This paper presents a modeling and simulation framework for tracked vehicles for ride comfort and load prediction analysis. The development began with the identification of the key issues such as formulations, integration schemes and contact (with friction) modeling on which the comparative studies are conducted. Based on the results of the investigations, the framework and process for the modeling and simulation of tracked vehicles are established and appropriate algorithms for contact and friction are developed. To facilitate the modeling and simulation process, a Python-based modeling environment was developed for process automation, design optimization and design of experiment. The developed framework has been successfully applied to the dynamic load predication of a M1A1 based Joint Assault Bridge (JAB). The parameter optimization enabled with the Python-based process automation tool helps improve the design and modification of vehicles for significantly improved fatigue life of suspension component.