Clinton, MI
Clinton, MI's wildfire risk, in USFS's own numbers
USFS scores Clinton at the 11th national percentile for wildfire risk to structures (among the lower wildfire-risk places nationally), a figure built from 1,144 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Clinton at the 11th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Clinton's building exposure, zone by zone
Only 11.8% of Clinton's 1,144 buildings carry Direct exposure and 0% carry Indirect; the remaining 88.2% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Clinton against the rest of the country
Clinton's 38th-percentile standing inside Michigan outpaces its 11th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Clinton ranks 28,052 for wildfire risk (1 is highest) and 10,998 by building count (1 is largest). Within Michigan alone, it ranks 462 of 745 places by risk. See the full county-by-county picture for Michigan on its state page.
What this risk score means for insurance
At the 11th national percentile, Clinton rates low for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Hardening a home in Clinton
Clinton's 88.2% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Clinton's figures come from
Every one of the two percentiles behind Clinton's 28,052-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Clinton's dominant minimal exposure actually means, with real examples from across the dataset.