Computational modeling of the human body is increasingly used to evaluate countermeasure performance during simulated vehicle crashes. During crash simulations, there are different injury criteria that can be calculated from such models and these can either be correlative (HIC, BrIC, etc.) or based on local deformation and loading (rib fracture, organ damage, etc.). In this study, we present a method to extract rib fracture data. The GHMBC M50-O (v. 4.3, 1.3M nodes, 2.2M elements, 76.8 kg) model was used in the simulations with rib fracture enabled and were run on a Linux cluster using 48 CPUs and MPP LS-DYNA. Rib fracture in the M50-O model is handled through element deletion once the element surpasses 1.8% effective strain over multiple time-steps. The algorithm central to the methodology presented extracts rib fracture data and requires 4-element connectivity to register a fracture. Furthermore, the fractures are localized to anatomical sections (Lateral, Anterior, and Posterior), rib level (1,2,3 etc.) and element strain data is recorded. Fractures crossing multiple anatomical sections were treated in each section but can be back calculated using a total fracture count. These were then visualized in a series of tables that were created for each time with fractures per each rib level and section depicted numerically and visually through an overlaid heat map. A total fracture count is also displayed at the bottom of each table for the each side. While correlative solutions for rib injuries are available, the methodology presented is for users who prefer to investigate rib fracture through element elimination. The techniques employed here mirrors methods presented in literature to determine real-world rib fracture location and patterns. A sample case with a nominal delta-V of 56.4 kph was examined for algorithm evaluation.