Hip resurfacing arthroplasty (HRA) is a type of hip replacement that removes minimal femoral bone stock and is most common in patients under 65 years of age. HRA patient outcomes can be improved with the use of preoperative planning. Preoperative planning is multifaceted and relies on joint morphology, applied loading, and material properties. These facets also interact in that morphology impacts loading, which impacts material properties and implant performance. Preoperative planning traditionally uses planar radiographs to measure morphology; however, using three-dimensional (3D) modalities could improve measurement accuracy. Sex impacts bone morphology, material properties, and loading; it is important that anthropometric data be disaggregated by sex, and sex-based analyses be conducted. This thesis aimed to design a 3D workflow to quantify and summarize the affects of proximal femur morphology on HRA patient outcomes. This study used the preoperative computed tomography (CT) scans and postoperative bloodwork of 219 HRA patients (202 males and 17 females) from the Kingston Health Sciences Centre dataset (ethics protocol SCOMP-007-11). A semi-automated workflow was designed and verified to quantify patient specific proximal femur morphology using 3D surface geometry from preoperative CT scans in HRA recipients. The proximal femur morphological parameters were measured due to their relevance in joint loading. Proximal femur morphological measurements were determined and summarized by both sex and affected side. Morphological measurements were compared to plasma cobalt and chromium ion rates, as they are used to quantify implant wear and failure. There is currently no workflow that quantifies mechanically motivated 3D proximal femur morphological parameters. This thesis proposes a novel methodology for assessing 3D proximal femur morphology, which can be used in combination with bone material properties and applied joint loading assessments for HRA preoperative planning.