Despite its relevance for law enforcement applications, the design of soft armor has mainly been based on a trial-and-error approach. A combined experimental and finite element analysis framework is used to build a predictive numerical model for the analysis and hence, design of soft armor. The material models for major components of the soft armor certification system—bullet, shoot pack, straps, and clay backing, are first constructed using laboratory tests and publicly available data. Next, three metrics, namely, back face signature (BFS), number of penetrated shoot pack layers, and mushrooming of the bullet, are established to gauge the model’s accuracy with respect to the laboratory ballistic test data. Finally, optimized material model parameters are obtained by calibrating a coarser model. The final accuracy test of the developed framework is carried out using laboratory ballistic test data involving multiple shots on the shoot pack. Subsequently, the impacts of incorporating stitching into the final model were examined and compared. The results indicate that reliable predictive data can be obtained using the developed process and can likely be extended for use in modeling other impact simulations.