Finite element human body models (HBMs) can be used to investigate injury mechanisms and tolerance of the human body during various loading conditions. The modeling complexity required to achieve good biofidelity in HBMs can lead to long compute times. This has prompted the development of faster running simplified models (GHBMC M50-OS) that can be used primarily for kinematic/kinetic comparisons. These simplified models share the same body habitus as the detailed counterparts, but with rigid bony structures and simplified modeling approaches for viscera, joints etc. Previous studies have shown the ability to modularly incorporate organs with high biofidelity models, such as the detailed (GHBMC M50-O) brain, into the simplified model. This technique allows for localized analysis of a region of interest in a fraction of the computational time required for the detailed model. The purpose of this study is to expand on this previous work by incorporating the previously-validated lower extremity of the M50-O into the computationally efficient M50-OS (M50-OS+LEx) and compare physical loading response to the M50-O in a localized knee bolster impact and a frontal sled simulation. The modularly-incorporated components include all deformable bony structures from the sacrum to the foot, detailed soft tissue structures from the femur flesh to the foot flesh, and all explicitly meshed tendons and ligaments. Total force from the femur, upper tibia, lower fibula, and ilium were obtained and compared between the two models during the knee bolster and frontal sled simulation. The implementation of the detailed lower extremity provided force time histories that tend to agree with the overall shape and magnitude of the data from the M50-O. The method introduced here, allows researchers to obtain similar force data at a much reduced computational cost (~71% time savings). Further investigation into the validation of this technique may include full vehicle buck simulations and optimization of included detailed components to ensure the best balance between time savings and performance.