WildfireRiskFinder

Maytown, KY

How exposed is Maytown to wildfire?

Very High
93rdpercentile nationally

Maytown's 169 buildings earn a 93rd-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Maytown's burn probability — fire likelihood with no building count factored in — sits at the 95th percentile nationally.

Where Maytown's buildings actually sit

169Total buildings
46.2%Direct exposure
53.9%Indirect exposure
0%Minimal exposure

169 buildings are counted in Maytown, and 53.9% of them are Indirect exposure — ember-driven risk rather than the 46.2% in Direct exposure or the 0% rated Minimal.

How Maytown compares

Maytown's risk sits at a similar level relative to Kentucky (96th percentile statewide) as it does nationally (93rd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Maytown ranks 2,366 for wildfire risk (1 is highest) and 26,069 by building count (1 is largest). Within Kentucky alone, it ranks 26 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.

Shopping for coverage in Maytown

At the 93rd percentile nationally, Maytown carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.

Lowering exposure, not just insuring around it

Maytown's 53.9% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.

Where Maytown's figures come from

Maytown's 93rd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Maytown's dominant indirect exposure actually means, with real examples from across the dataset.