Carbon fiber running-specific prostheses (RSPs) are widely used among lower-limb amputee runners. However, which prosthesis provides the best performance for runners remains unknown. For this purpose, a computational model of the human body with a prosthesis was created and the effect of the prosthetic parameters on performance was investigated. First, motion capture systems were used to collect motion data from amputees. Furthermore, marker and force plate data were obtained to create a digital human model. Kinematic data such as limb lengths and joint angles were calculated using marker data. Afterward, the inertial properties were estimated to conduct inverse dynamic analyses. After building a computational model of amputee sprinting, the joint positions and ground reaction forces (GRFs) were compared with the experimental results. The design parameters of the prosthesis were introduced to understand the effects of the prosthesis on motion and performance. The response surface method was used to express motion adaption regarding the geometry and stiffness of the prosthesis. Hip and knee sagittal joint angles were updated based on the response surface method to simulate joint motion adaptations of the worn prosthesis. Additionally, average horizontal velocity, horizontal velocity change over one gait cycle, vertical and horizontal impulses were considered as performance functions. An evaluation parameter was proposed to generalize the idea of performance. The moment of the prosthetic knee and the closest point of the prosthesis to the ground during the swing phase were defined as design constraints to consider knee buckling and prosthetic leg tripping, respectively. The effect of the design parameters on the performance and constraint functions was also investigated and a method to determine and design a suitable prosthesis for an individual was proposed. It was revealed that proper selection and design of prostheses represent an important way to increase performance.