Abstract: OBJECTIVE To explore the influencing factors of surgical site infection (SSI) in patients undergoing microvascular decompression (MVD) for trigeminal neuralgia, and to construct and validate a nomogram prediction model. METHODS Clinical data of 462 patients with trigeminal neuralgia, who underwent MVD in the Department of Neurosurgery at Jining No. 1 People's Hospital from Jan. 2022 to Dec. 2024, were analyzed. The patients were randomly divided into a training set (n=323) and a validation set (n=139) at a ratio of 7∶3. Multivariate logistic regression analysis was used to screen independent risk factors, and a nomogram prediction model was constructed and validated. RESULTS The incidence of SSI after MVD for trigeminal neuralgia was 12.12% (56/462). Logistic regression analysis identified the following influencing factors for SSI after MVD: hypoalbuminemia (OR=3.316), operation time (OR=1.016), hospital stay (OR=1.233) mastoid air cell opening (OR=2.580) and prophylactic use of antibacterial agents 0.5-1h before surgery (OR=0.232). The Hosmer-Lemeshow (H-L) test values for the constructed nomogram prediction model in the training and validation sets were P=0.651 and P=0.974, respectively, indicating good model fit. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.917 (95%CI: 0.879-0.955) for the training set and 0.954 (95%CI: 0.913-0.995) for the validation set, demonstrating good discriminative ability. Calibration curves showed good consistency in both models, and decision curve analysis (DCA) indicated high clinical utility value of the two models. CONCLUSION The nomogram-based risk prediction model for SSI after MVD for trigeminal neuralgia exhibits strong predictive performance and high clinical utility value, aiding in early identification of high-risk patients and targeted interventions.