Bone is a dynamic structure capable of adapting its shape and architecture to carry consistently applied loads with a minimum amount of material. As a result, the density distribution within bone contains direct information about these loads. In the following dissertation the linear density-based load estimation method was implemented and applied to two-dimensional coronal slices of the proximal femora of a chimpanzee, gorilla, grizzly bear and lion. In order to maintain the three-dimensional characteristics in the two-dimensional models, a back-plate was added to the diaphysis of each femora. A parametric study was performed on the back-plate to identify the effects of various parameters on the overall solution. As a result of this study, a simple method based on the geometry of bone is proposed for selecting the back-plate parameters. The results of the linear analysis indicated that the magnitude-weighted load directions may correlate to different modes of locomotion. However, There are limitations to the linear method. The linear method relies on assumed pressure distributions, which do not necessarily represent in-vivo pressure distributions. To address this issue, a contact algorithm was developed to model the interaction between the acetabular cup and femoral head. This not only produces physiological pressure distributions on the femoral head, but it also allows the pressure distributions to be associated with specific relative positions of the pelvis and femur, both of which are impossible using the linear method. Trends in the magnitude-weighted load direction from the contact algorithm are similar to the results from the linear method. Forward remodeling simulations illustrate that the loads determined from the contact algorithm and linear method are capable of producing key aspects of the density patterns found in the metaphysis of the femora. When compared to the results of the linear analysis, the density distributions from the contact algorithm better match the actual density distributions in the case of the lion and grizzly.