Virtual planning of surgical procedures will be the future in a world where personalized patient care is on the rise. To boost this transition in the treatment of kidney cancer, we propose an interactive, patient-specific tool that guides surgeons towards the most optimal surgical approach to improve patient outcome as well as patient involvement and education (to make patients better understand their own pathology and surgery). The virtual planning tool will start from a CT-scan. By means of an in-house developed and trained deep learning network, the kidney and corresponding relevant structures will be automatically segmented. After 3D reconstruction, the latter will result in a 3D model as input for the next steps. Analysis of renal metrics will elucidate the complexity of the patient case and intended surgery. 3D perfusion zone simulations will assist in determining the optimal clamping approach. Combining these steps will result in a well-founded suggestion of the optimal surgical approach. Integrating this workflow in a user-friendly tool will improve both patient outcome and patient-doctor communication.