WildfireRiskFinder

Forest, IN

Forest wildfire risk explained

Low
1stpercentile nationally

USFS's Wildfire Risk to Communities model puts Forest at the 1st national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 221 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Forest's burn probability — fire likelihood with no building count factored in — sits at the 1st percentile nationally.

Where Forest's buildings actually sit

221Total buildings
27.2%Direct exposure
0%Indirect exposure
72.9%Minimal exposure

Most of Forest's buildings (72.9% of 221) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.

Forest against the rest of the country

There's little gap between Forest's 1st national percentile and its 3rd percentile inside Indiana, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Forest ranks 31,359 for wildfire risk (1 is highest) and 24,075 by building count (1 is largest). Within Indiana alone, it ranks 935 of 967 places by risk. See the full county-by-county picture for Indiana on its state page.

Shopping for coverage in Forest

Forest's low rating (1st percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.

What would actually reduce this score

Forest's 72.9% 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 Forest's figures come from

Every one of the two percentiles behind Forest's 31,359-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Forest's dominant minimal exposure actually means, with real examples from across the dataset.