The objective of this research is to develop a new paradigm in fire-fighting techniques and demonstrate the feasibility of using fire imaging technology (e.g., thermal imaging cameras to monitor smoke conditions from a burning building) combined with fire modeling software for real-time fire analysis to assist firefighter operations. This project focuses on the development of a prototype inverse fire modeling (IFM) algorithm. The IFM uses: MATLAB as the programming language; BRI2002 as the zone model; and a genetic algorithm for optimization. The IFM is tested as a stand-alone component in which the camera-based observations of smoke layer properties are replaced by data on the upper layer temperature (TUL) coming from a reference BRI simulation with a certain heat release rate (HRRref). The objective of the IFM algorithm is then to provide an estimate of HRRref from the sole knowledge of TUL. The performance of the IFM algorithm has been studied in a series of tests of gradually increasing complexity.