Biomechanical finite element simulations are becoming increasingly popular and essential for evaluating healing potential and making early predictions in clinical and research settings. A key factor influencing the accuracy of these simulations is the origin and quality of the data. It is already known that the segmentation of the data has an influence on the simulation [1]. But what about the origin of the data for the computational model? This study investigates the impact of three distinct implant data types on simulation outcomes: segmented implant data derived from a computed tomography scan, reverse-engineered implant data obtained through 3D scanning of an implant, and the original dataset provided by the manufacturer. The goal is to determine how the choice of data type affects simulation accuracy. Segmented implants eliminate the need for alignment within the bone model but may lose critical features, such as screw threads, due to smoothing processes. Reverse-engineered implants offer greater detail but are influenced by the quality of the 3D scanner and the reconstructed surface, with noise and scan artefacts potentially compromising precision. Manufacturer-provided datasets retain the original geometry but require manual alignment with the bone model, introducing additional variables that affect the simulation's outcome. The study is based on a segmented dataset of a radius with an artificially generated fracture (AO Classification Type 2R1A2) derived from a computed tomography scan. Each implant type was integrated into the bone model, and clinically relevant load scenarios were simulated. Results were evaluated based on mechanical parameters such as deformation, strain and stress distribution. This study underscores the critical role of implant data type in ensuring the reliability and interpretability of biomechanical simulations. The findings provide valuable guidance for researchers and engineers working on patient-specific implant development and biomechanical analyses, highlighting the trade-offs between data detail and simulation fidelity.