A property price predictor built on real marla and kanal data.
Sweet Properteez is a property price predictor for Pakistan’s housing market: enter a property’s size, location and type, and get an instant, AI-assisted valuation with a confidence range — the same instinct a good local broker has, minus the incentive to talk the number up.
What is a property price predictor, exactly?
A property price predictor is software that estimates what a specific property is worth by comparing its size, location and features against patterns in known sale prices — the same logic a seasoned agent uses when they say “that’s a 30-lac house,” except systematic, auditable, and not tied to their commission. Sweet Properteez is built as a property valuation tool for Pakistan specifically, because Pakistan prices property in units — marla and kanal — that most global valuation software simply doesn’t understand, and because Pakistan’s market has pricing quirks (more on those below) that a generic international tool would miss entirely.
The version live today is a working demonstration: the pricing logic is transparent and documented in the page source, and it runs entirely in your browser. As we collect verified transaction data from Lahore and beyond, that logic gets replaced by a trained model — same interface, better numbers underneath.
A calculator just does arithmetic on the numbers you give it. A predictor is expected to be right about a property it has never seen before, based on patterns learned from properties it has. That’s a higher bar, and it’s the one we’re building toward.
How our instant home value estimator works
Three inputs, one number with its range — the whole product is this flow, done properly, rather than a calculator bolted onto a landing page.
Choose your city
We start with Lahore, because it has the transaction volume to make a model worth building and the pricing inconsistency to make it worth using. Every city on Sweet Properteez gets its own model rather than one national average, because a per-marla rate in Lahore says nothing useful about Multan or Karachi.
Enter the property’s specs
Size in marla or kanal, the specific society or block, property type (house, flat, or plot), and bedroom count. This is deliberately the same short list of questions a broker would ask on a first phone call — nothing more, nothing that requires you to already know the answer you’re looking for.
Get an instant estimate, with its range
Rather than a single confident number, our instant home value estimator returns a price range and a confidence score, plus a breakdown of what’s pushing the estimate up or down — location premium, size, property type, bedroom count. A single number pretending to be exact is usually the least honest part of a property valuation.
“Instant” here means what it sounds like: the estimate recalculates the moment you change an input, with no form submission, no email gate, and no waiting for a callback from an agent.
Why an AI-powered house price calculator online beats broker guesswork
Most people’s only option for a house price calculator online is asking two or three agents and averaging what they say — and agents have an obvious incentive to quote high to sellers and low to buyers. A model has no such incentive. It weighs the same inputs a broker would (location, size, property type, condition proxies like bedroom count) but does it the same way every time, on every property, whether or not there’s a commission attached to the answer.
This is also what “real estate price prediction AI” actually means in practice, stripped of the marketing gloss: a model trained on historical sale prices learns how much each factor typically moves the price in a given market, then applies those learned weights to a new property it hasn’t seen. It’s pattern recognition, not magic — which is exactly why it needs real transaction data to be trustworthy, and why we’re upfront that today’s Lahore numbers are placeholder rates until that data is in.
The strength of a price-prediction model is entirely a function of the data it’s trained on. A model trained on thin or stale data will sound just as confident as one trained on thousands of verified sales — which is why we publish our current data status openly instead of dressing up placeholder rates as a finished product.
Three specific gaps in how Pakistani property gets priced
Not “no reliable data” in the abstract — these are the actual mechanics that make a fair number hard to get, and the reason a purpose-built property valuation tool is worth having.
DC vs market rate
The government’s DC/FBR valuation table — used to calculate transfer tax — sits far below what property actually sells for in almost every society. It’s a useful figure for the Federal Board of Revenue and a nearly useless one for a buyer or seller trying to agree on a fair price.
On-money
A large share of the real price in most transactions is paid as undocumented cash on top of the registered sale deed. That means the “official” price on record is rarely close to the real one, and any tool that only looks at registry data is working from a skewed baseline.
No cross-society index
Per-marla rates aren’t published across DHA, Bahria Town, Gulberg and the rest on one shared, comparable scale. Each society’s going rate lives in a different broker’s head, updated informally and inconsistently, which makes even honest brokers bad at pricing outside their own patch.
Who actually uses a property valuation tool
A property price predictor isn’t only useful at the moment of buying or selling — it’s useful anywhere someone needs a defensible number instead of a guess.
Buyers
Checking whether an asking price is in line with the area before making an offer, without needing to interview five brokers first. A buyer who walks into a negotiation with an independent range from a property valuation tool is negotiating from a documented position instead of a gut feeling — and sellers notice the difference.
Sellers
Setting a listing price that’s realistic enough to sell in weeks rather than months, instead of anchoring on what a neighbour claims they got. Overpricing by even 10% on a marla-for-marla basis is enough to leave a listing stale for a season in most Lahore societies, which costs more in the end than a slightly conservative opening number.
Agents
Backing up a verbal quote with a documented range when a client pushes back — a second opinion that isn’t the agent’s own opinion. Several agents already treat the Lahore estimate as a sanity check before quoting a new client, precisely because it doesn’t carry their commission incentive.
Investors
Comparing prospective purchases across societies on the same scale, rather than trusting each seller’s own framing of “good value.” A house price calculator online that treats DHA, Bahria Town and Johar Town consistently makes it possible to actually compare yield and appreciation potential across a shortlist, not just compare asking prices.
Factors that affect property value in Pakistan
Every property price predictor, ours included, is really just a structured way of weighing the same handful of factors a human already intuitively considers. Making them explicit is what turns intuition into something you can check and argue with.
Location, at the society and block level
Location is consistently the single largest driver of price in Pakistani real estate — often larger than size itself. A 10-marla plot in Gulberg and the same plot in Wapda Town can differ by more than double, not because of anything physically different about the land, but because of proximity to commercial areas, road width, development phase, and simple prestige. Our model treats each covered society’s per-marla rate as a distinct input rather than averaging the city, because that averaging is exactly what makes generic valuation tools unreliable in Pakistan.
Size, in marla and kanal — not square feet
Because Pakistani listings are quoted in marla and kanal, a valuation tool that only accepts square feet forces the user to convert first, introducing rounding errors before the estimate even starts. One kanal equals 20 marla, and 1 marla is roughly 225 square feet, though the exact conversion varies slightly by province and by whether a plot is measured by the old or revenue-department standard. Our calculator accepts marla or kanal natively and converts internally, so the number you enter is the number that actually appears on the file.
Property type: house, flat, or plot
An undeveloped plot, a built house, and a flat on the same land area price differently because they represent different amounts of embedded construction cost and different buyer pools. A plot is priced almost purely on location and size; a house adds the value (and depreciation) of what’s built on it; a flat trades some land-value upside for lower maintenance and, often, a lower entry price per marla-equivalent.
Bedrooms and layout, as a proxy for usable space
Bedroom count is a rough but genuinely useful proxy for how efficiently a house’s covered area is used — two 10-marla houses with different bedroom counts are rarely equally desirable to the same buyer. It’s a smaller factor than location or size, but it’s not a decorative one, which is why it appears in the model’s factor breakdown rather than being ignored.
Whether it’s a bank’s valuator, a broker’s gut estimate, or a real estate price prediction AI, every property valuation method is ultimately comparing a property to similar recent sales and adjusting for what’s different — the only real distinction is how systematically and transparently that comparison is done.
How the confidence score and price range are calculated
Every estimate on Sweet Properteez comes back as a range with a confidence percentage attached, rather than a single figure — that’s a deliberate design choice, not a hedge. Real property valuation methods, whether run by a bank, a broker, or a real estate price prediction AI, always carry uncertainty, and pretending otherwise is how “confidently wrong” tools earn their reputation.
The range is built by widening the point estimate by a fixed margin in either direction, giving you a realistic band rather than a false-precision decimal. The confidence percentage moves with how typical the inputs are for the market it’s covering: a 10-marla, 3-to-4-bedroom house in a covered Lahore society sits near the center of what the model has strong signal on, so confidence is highest there; sizes and configurations further from that typical range get a lower confidence score, because there’s less to compare them against. This is the same reasoning a good appraiser uses instinctively — more certain about a run-of-the-mill 10-marla house than a 2-kanal outlier — made explicit instead of left as a feeling.
A tool that hides its uncertainty isn’t more accurate, it’s just less honest about being wrong. Showing the range and the confidence score together is what makes an instant home value estimator something you can actually rely on for a real decision.
One country live. One city priced.
Lahore has its own trained pricing logic. Every other city on this list is a page in place and a model not yet trained — not a live estimate.
Lahore
DHA, Gulberg, Model Town, Bahria Town, Johar Town, Wapda Town — six areas with their own priced rates, ready to search.
6 areas priced Page live, model pendingKarachi · Islamabad · Faisalabad · Rawalpindi · Multan
See property prices Pakistan →Each of those five cities already has a page describing its market and why it isn’t priced yet — Karachi’s sheer transaction volume, Islamabad’s sector-based addressing, and so on. Visit the property prices Pakistan page for the full breakdown city by city, including what’s blocking each one from getting its own trained model next.
Questions about the property price predictor
Is Sweet Properteez a real estate price prediction AI, or a fixed calculator?
Today it’s a transparent, documented pricing formula — a working demonstration of the flow, not a trained model. The roadmap is a proper real estate price prediction AI trained on verified Lahore transactions, using the same interface you see now.
Is the house price calculator online free to use?
Yes. Estimates on the Lahore page are free, instant, and don’t require an account, email, or phone number.
Which cities does the property valuation tool cover right now?
Lahore is the only city with a working model today. Karachi, Islamabad, Faisalabad, Rawalpindi and Multan have pages mapped out but no trained pricing yet — see the Pakistan page for details on each.
How accurate is the instant home value estimator?
As accurate as its inputs allow, and no more. The current Lahore figures are placeholder rates, not live transaction data, so treat today’s numbers as a demonstration of the range-and-confidence format rather than a certified valuation.
Does the property price predictor work in marla and kanal?
Yes — that’s the reason it exists. Size inputs are natively in marla or kanal (1 kanal = 20 marla, roughly 4,500 sq ft), not square feet, matching how Pakistani property is actually bought and sold.
Can I use this as a broker or agent?
Yes — several agents already use the Lahore estimate as a second, non-commissioned reference point when a client questions a verbal quote.
What data does the property price predictor use today?
The current version runs on documented illustrative rates per area rather than a live feed of verified sales — we’ve been explicit about this throughout the site rather than presenting placeholder numbers as finished data. Real transaction data collection for Lahore is the next milestone before Karachi.
Why isn’t there a national average property price for Pakistan?
Because it wouldn’t mean anything useful. Property prices Pakistan-wide range from a few lac per marla in smaller towns to tens of lac per marla in premium Lahore or Karachi societies — a single national number would hide more than it reveals, which is exactly why this tool works city by city and society by society instead.
Does the tool account for on-money or under-declared prices?
The pricing logic is built around realistic market rates, not the artificially low DC/FBR figures used for tax purposes — so estimates are meant to reflect what a property would actually transact for, on-money included, rather than what appears on a registered sale deed.
See what a Lahore property is really worth.
Punch in the specs and get an instant estimate with a real confidence range — not a broker’s opening offer.
Estimate a Lahore property