Project Scope & Cost Estimator

First, it starts with a room/project “base cost” for a Partial remodel (size index = 1, Standard quality, average site conditions). Then it applies multipliers for your chosen scope level, scales up/down with your size index using a remodeling-style exponent, adjusts for Value/Standard/Premium quality, and finally multiplies by the site condition factor (to reflect hidden issues and access difficulty). The result is an estimated base total, then the calculator widens or tightens the band using a complexity/risk score.

A wider band doesn’t just mean “more expensive”—it means your project is more variable and less predictable given the inputs (scope + room type + site conditions + quality). For example, Full remodels in renovation-heavy rooms and high site-condition multipliers (older systems, difficult access, more hidden defects) typically increase schedule risk and uncertainty. The cost split (labor vs materials vs overhead) is provided as context so you can see what’s driving the estimate, not as a guaranteed accounting breakdown.

Be careful when choosing Repair for Whole home (and often Kitchen/Bathroom): this scope can miss replacement-level work, so the calculator will show a caution that the band may be underestimated. Also note that the “quality tier” is meant to match how you’re likely selecting finishes—Premium finishes on a Repair scope may price closer to Partial depending on demolition extent. If your site condition multiplier is high (above ~1.35), expect the tool to widen the band to reflect hidden issues.

If your project size index is outside the allowed range (0.5–3.0), the calculator clamps it and flags that the size index was adjusted. If you pick combinations that don’t align well with typical scope definitions (e.g., Repair + high site-condition multiplier + Premium), treat the low end as optimistic and use the high end to guide contingencies. For very small projects (size near 0.5), consider that bands can still be meaningfully wider in real life due to mobilization and minimum-fee realities—even if the math starts from generalized “typical” assumptions.