Abstract:Background and Aims Bile leakage is a common and clinically significant complication after laparoscopic cholecystectomy (LC), which may delay recovery and increase the need for reintervention. This study aimed to identify risk factors for bile leakage after LC and to develop a predictive regression model.Methods A retrospective analysis was conducted on 1 630 patients who underwent LC between September 2020 and May 2025. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors, and a predictive model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) analysis.Results Bile leakage occurred in 81 patients (4.97%). Multivariate analysis identified common bile duct diameter ≤3 mm, gallbladder neck stones, anatomical variation, Calot's triangle adhesion, adhesion to surrounding organs, gallbladder wall thickness ≥5 mm, and electrocautery in Calot's triangle as independent risk factors (all P<0.05). The regression equation was: Logit (P)=-9.126+1.362×gallbladder neck stones +0.784×CBD diameter+1.695×adhesion to surrounding organs +1.108×electrocautery+0.895×Calot adhesion +0.679×anatomical variation +0.559×wall thickness. The model showed good discrimination with an AUC of 0.903, sensitivity of 82.72%, and specificity of 84.44%.Conclusion Multiple anatomical and intraoperative factors are associated with bile leakage after LC. The proposed regression model demonstrates good predictive performance and may assist in perioperative risk assessment.