How to Find After-Repair Value (ARV) by Address

Yes — but not from the address alone. The address identifies the subject property: its size, age, and location. The value comes from somewhere else entirely: recently sold, renovated homes nearby. Any tool that turns an address into an After-Repair Value is doing comparable-sales work behind the scenes — pulling nearby sales and scaling them to your property’s square footage.

That matters because it tells you what to check. An address-based estimate is only as good as the comparable sales behind it — how recent they are, how close, and whether they were genuinely renovated when they sold. There is no shortcut around the comps — only faster ways to assemble them.

Start with what the address pins down: the subject’s square footage — and what it will be after the renovation, since an addition changes the math. Then pull three to six recently sold, renovated homes within about a mile, similar in size, age, and condition.

Divide each sale price by its square footage to get a price per square foot, average those figures, and multiply the average by the subject’s post-renovation square footage. The result is the property’s After-Repair Value.

Illustrative example. The subject will be 1,600 square feet after renovation. Three nearby renovated sales work out to $195, $210, and $225 per square foot — an average of $210. The After-Repair Value estimate is $210 × 1,600 = $336,000. With a $45,000 rehab quote, the 70% Rule caps the offer at ($336,000 × 70%) − $45,000 = $190,200.

The slow part was never the multiplication — it is assembling trustworthy comparable sales for one specific address. Fundry does that step on any Georgia address: type the address, pick your strategy — flip, ground-up, or rental — and the comparable sales are pulled for you. You curate which homes count, and the resale estimate recalculates live as you toggle comps in and out. No black box.

Fundry is free. No credit card. No trial. It works on the web and as an iOS app, so the numbers are ready before you have finished walking the property.

Most bad address-based estimates trace back to one of three problems. The first is thin or stale data: two comparable sales, or sales from a year ago, tell you what the market was — not what it is. Treat a thin comp set as a wider range, and expect an honest tool to say so rather than hide it.

The second is condition mix. One unrenovated sale in the average drags the price per square foot down and understates the resale estimate; a brand-new construction sale can inflate it just as easily. Every comp should answer the same question: was this home in the condition mine will be in when it sells?

The third is square footage. The multiplication magnifies any error — in the illustrative example above, being off by 200 square feet moves the estimate by $42,000. Verify the number against county records and the listing before trusting the result.