New Milford, IL
New Milford wildfire risk explained
New Milford sits at the 16th percentile nationally for wildfire risk to structures — among the lower wildfire-risk places nationally — per USFS's Wildfire Risk to Communities model, built from its 545 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, New Milford's burn probability — fire likelihood with no building count factored in — sits at the 17th percentile nationally.
What "at risk" means for the buildings here
75.8% of New Milford's 545 buildings sit in USFS's Minimal exposure zone, with only 24.2% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Where New Milford ranks
Within Illinois, New Milford ranks higher (55th percentile) than it does nationally (16th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, New Milford ranks 26,337 for wildfire risk (1 is highest) and 16,635 by building count (1 is largest). Within Illinois alone, it ranks 646 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.
New Milford and the insurance market
New Milford's low wildfire rating (16th 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.
Lowering exposure, not just insuring around it
New Milford's 75.8% 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 New Milford's figures come from
New Milford's 16th-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 New Milford's dominant minimal exposure actually means, with real examples from across the dataset.