Machine learning tools can now help surgeons assess the risk of postoperative complications in acute calculous cholecystitis patients.

• Cholesurgrisk I achieved an AUC-ROC of 0.8456, while Cholesurgrisk II, which includes intraoperative data, improved this to 0.8903.
• A web-based version of Cholesurgrisk I offers real-time, patient-specific risk estimates.

Integrating these models into practice could enhance preoperative assessments and significantly improve patient outcomes.