Objective: To explore the risk factors for chronic pain after single-port video-assisted thoracic surgery (VATS), establish the predictive model and validate it. Method: A retrospective analysis was conducted on 302 patients who underwent single-port thoracoscopy surgery at Nanjing Chest Hospital from January 2023 to June 2023, clinical data of patients were collected using a numerical rating scale（NRS） assessed the degree of pain in patients three months after surgery and divided them into a pain group and a non pain group. Randomly divided into a training set (n=214) and a validation set (n=88) according to a 7:3 ratio, and single factor analysis was performed on the training set.Logistic regression analysis is used to establish a predictive model based on the receiver's work characteristics. Operator characteristic (ROC) curve evaluation model discrimination, calibration curve evaluation model consistency, decision curve analysis (DCA) evaluate the clinical value of the model, and verifying the model in the validation set. Result: Multivariate analysis showed that age (OR=0.925, 95% CI=0.872-0.981, P=0.009), postoperative closed chest drainage time (OR=1.273, 95% CI=1.018-1.591, P=0.034), C-reactive protein value (CRP) on the first day after surgery (OR=1.090, 95% CI=1.030-1.153, P=0.003), and NRS score on the first day after surgery (OR=3.060, 95% CI=1.879-4.981, P<0.001) were independent risk factors for chronic pain after single-port thoracoscopy. Based on this, a prediction model was constructed, with an area under the ROC curve of 0.871 (95% CI=0.799-0.943) and a maximum Yoden index corresponding to 0.195. (0.856, 0.765). With a Bootstrap sample of 1000 times, the predicted risk of chronic pain by the calibration curve was highly consistent with the actual risk. The DCA curve indicates positive returns at all predicted probabilities, indicating good clinical value. Conclusion: After single-port video-assisted thoracic surgery, patient age,time of closed thoracic drainage after surgery, CRP value on the first day after surgery, and NRS score on the first day after surgery are all risk factors for chronic postoperative pain. This prediction model is helpful in accurately predicting chronic postoperative pain and has good clinical application value.