Wilsall, MT
Wilsall wildfire risk explained
USFS's Wildfire Risk to Communities model puts Wilsall at the 57th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 259 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Wilsall at the 55th percentile, close to its 57th-percentile risk score.
Where Wilsall's buildings actually sit
Most of Wilsall's buildings (61.8%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Wilsall against the rest of the country
Wilsall's 57th national percentile looks worse in isolation than its 21st ranking inside Montana does — this place is on the milder end for its own state, by 36 points. Among the 31,521 US communities USFS scores, Wilsall ranks 13,587 for wildfire risk (1 is highest) and 22,859 by building count (1 is largest). Within Montana alone, it ranks 374 of 475 places by risk. See the full county-by-county picture for Montana on its state page.
What this risk score means for insurance
At the 57th national percentile, Wilsall rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Wilsall's 61.8% 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 Wilsall's figures come from
Wilsall's 57th-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 Wilsall's dominant indirect exposure actually means, with real examples from across the dataset.