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Bone metastases result from a primary tumor metastasizing, causing tumors to form at different anatomical locations. These secondary tumors can appear on the bone and are a result of a disrupted balance between osteoblasts and osteoclasts. Bone metastases cause pain and can affect the range of motion. They can be reduced using radiotherapy in combination with osteosynthetic drugs. However, in some cases the lesion is too large whereby it could affect the strength of the femur. A surgical intervention should then be done to strengthen the bone before a fracture occurs. Current procedures for assessing fracture risk have unsatisfactory diagnostic values. For instance, the Mirels score has a Sensitivity of 91% and Specificity of 35%. The axial cortical involvement threshold has a Sensitivity of 83% and a Specificity of 50%. Low Specificity implies that these measurements incorrectly identify more people as having a high fracture risk. Finite Element Analysis (FEA) could play an important role in improving the specificity. This paper builds upon previous research by Sas (2021), who developed a fully automated workflow for fracture risk assessment of the metastatic proximal femur. A nonlinear material model is used to describe the mechanical properties of bone tissue. The nonlinear Finite Element simulations were solved using a incremental displacement method. Building upon this method, different loading conditions were applied to the femur head after which the failure load is assessed. Failure load is defined as the maximum force in the force-displacement curve. A critical threshold was determined by optimizing the sum of the Sensitivity and Specificity. A threshold of 8.5 × BW was found, resulting in a Sensitivity of 92% and a Specificity of 68%. A minor improvement over the original model by Sas (2021), showing the robustness of the original model.