Optimal settings and designs for prosthetic parameters, such as knee stiffness, are required to achieve effective and stable sit-to-stand (STS) movements for individuals with lower limb prostheses but remain inadequately defined. One possible solution is prosthetic modeling and predictive simulations. However, current literature primarily focuses on inverse kinematics, inverse dynamics, and most likely, gait. There remains a gap in optimizing the parameters during STS movement through predictive simulation. By utilizing SCONE (Simulated Controller OptimizatioN Environment for predictive simulating), this study aims to find the optimized prosthetic parameters and investigate the effect of varying transfemoral prosthetic knee joint stiffness on biomechanics and validate this approach. A modified musculoskeletal model with a prosthesis and neuromuscular controllers are combined for predictive sit-to-stand simulation. The control parameters for neuromuscular controllers and the prosthetic parameters are optimized by SCONE with predefined objective functions to obtain energy-oriented results. The simulation results were analyzed in terms of joint load, stability, kinematics, and energy cost. Lastly, the results were validated by comparison with an existing experimental dataset. The simulations indicated that prosthetic knee stiffness affects joint loads, stability, kinematics, and energy expenditure during STS movements. Higher knee stiffness generally leads to increased prosthetic side joint loads and contribution but requires higher damping ratios to ensure a successful STS movement, while extreme stiffness should be avoided. Optimal stiffness settings were identified near 70 Nm/rad with the damping ratio of 22 Nms/rad. Validation shows the feasibility of this approach as well as its limitations. This study demonstrates the potential and insights of predictive simulations in optimizing prosthetic knee parameters. However, the current approach is limited by the model, methodological, theoretical, and practical issues. Therefore, further validation and refinement are necessary. Future work may focus on building complex and customized models and exploring other movements.