Generic elbow prostheses often fail to meet the specific anatomical needs of patients, leading to high misalignment rates in Total Elbow Arthroplasty (TEA). This misalignment negatively impacts surgical efficiency, patient satisfaction, and critical functional outcomes, including range of motion and load-bearing capacity. Although personalized prostheses could address these challenges, current practices rely on ad-hoc intraoperative adjustments that frequently fall short of meeting individual anatomical requirements. A key obstacle to achieving truly personalized designs is the absence of a quantitative method for evaluating alignment. To tackle this issue, we developed a 3D computational model to simulate TEA and introduced the Alignment Improvement Metric (AIM), a novel quantitative tool for assessing prosthesis alignment. Using AIM, we designed three personalized prosthesis approaches optimized for individual, group, and cohort scenarios. Computational validation on 120 clinical participants demonstrated an average alignment improvement of up to 30% with just 3 prostheses, highlighting the potential of this AI-driven solution to enhance TEA outcomes and patient satisfaction.