Wildfires are gaining more attention every year as they burn more frequently, more intensely, and across larger landscapes. Generating timely estimates of forest resources within fire perimeters is important for land managers to quickly determine the impact of fi res on U.S. forests. The U.S. Forest Service’s Forest Inventory and Analysis (FIA) program needs tools to produce these estimates in a timely matter. Small-area estimation methods were recently developed and applied to previous wildfires in Colorado. This paper illustrates how these methods were assimilated into an automated R-based programming environment, FIESTA, to produce estimates of forest resources affected by a specified fire perimeter. This small-area estimation approach uses a modified composite estimator, which is a weighted average of two estimators: a synthetic estimator built from model-based predictions, and a direct estimator built from the FIA plot data that fall within the small area. The synthetic estimator is generated from FIA sample data and Landsat geospatial layers (www.landfire.gov) that fall within a larger area encompassing the small area, delineated by the Forest Service EcoMap Subsections.