Terry, MT
Terry wildfire risk explained
USFS scores Terry at the 77th national percentile for wildfire risk to structures (well above the national norm for wildfire risk), a figure built from 646 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Terry at the 76th national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Terry's buildings actually sit
Most of Terry's buildings (94.6%) 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.
How Terry compares
Terry's 77th national percentile looks worse in isolation than its 49th ranking inside Montana does — this place is on the milder end for its own state, by 29 points. Among the 31,521 US communities USFS scores, Terry ranks 7,127 for wildfire risk (1 is highest) and 15,247 by building count (1 is largest). Within Montana alone, it ranks 243 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 77th percentile nationally, Terry carries the 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.
Hardening a home in Terry
Because 94.6% of Terry's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Terry's figures come from
Every one of the two percentiles behind Terry's 7,127-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Terry's dominant indirect exposure actually means, with real examples from across the dataset.