This paper presents a comprehensive application of an automated surgical planning workflow for bone tumor resection, integrating two previously developed algorithms into a real clinical case. The study focuses on a patient with a left tibial osteosarcoma, demonstrating how the automated framework streamlines the entire preoperative process, from tumor resection planning to allograft selection. The cutting plane optimization tool reduced manual planning time from hours to just 19 min while ensuring complete tumor removal with minimal healthy bone resection. For reconstruction, the system automatically reconstructed the patient’s premorbid anatomy and selected the best-matched allograft from a virtual donor database, achieving a high degree of anatomical precision (mean distance: 0.29 mm). The results highlight the clinical potential of this integrated approach, which improves efficiency, reduces subjectivity, and enhances reproducibility in complex bone tumor surgeries.