Digital twin technology offers significant benefits for addressing fracture non-unions in orthopedic trauma surgery, particularly in cases requiring revision surgery. In this study, we developed a clinically applicable digital twin workflow that integrates patient-specific imaging, motion capture, musculoskeletal modeling, and finite element simulation. We applied this workflow to five real patient cases involving different anatomical sites and treatment strategies, including implant modification, augmentative fixation, and corrective osteotomy. Each case was virtually reconstructed to evaluate mechanical conditions before and after revision surgery. The results demonstrated that digital twins can predict improvements in implant stress distribution and fracture strain states, offering valuable insights for optimizing surgical decisions. This work highlights the feasibility of digital twins and their clinical value in supporting individualized revision strategies, laying the foundation for their broader use in trauma care. .