Perrinton, MI
Perrinton wildfire risk explained
Perrinton's 261 buildings earn a 3rd-percentile wildfire-risk score nationally under USFS's model — among the lower wildfire-risk places nationally. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Perrinton at the 3rd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
Where Perrinton's buildings actually sit
USFS classifies 81.6% of Perrinton's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 18.4% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Perrinton against the rest of the country
There's little gap between Perrinton's 3rd national percentile and its 5th percentile inside Michigan, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Perrinton ranks 30,641 for wildfire risk (1 is highest) and 22,802 by building count (1 is largest). Within Michigan alone, it ranks 710 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
Perrinton's low wildfire rating (3rd percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in Perrinton
Even with 81.6% of Perrinton outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Perrinton's figures come from
Every one of the two percentiles behind Perrinton's 30,641-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Perrinton's dominant minimal exposure actually means, with real examples from across the dataset.