Objective This study aims to develop a predictive model for postoperative recurrence risk and identify significant risk factors following myomectomy in patients with uterine fibroids. Methods A retrospective analysis was conducted on 208 patients who underwent myomectomy at the First Affiliated Hospital of Bengbu Medical University between January and June 2022. Clinical parameters including age, parity, menarche age, body mass index (BMI), fibroid characteristics (type, number, diameter), surgical approach, and histopathological findings were evaluated. The patients were divided into the recurrence (n=59) and non-recurrence (n=149) groups according to whether there was recurrence after surgery. The postoperative recurrence rate was calculated. Multivariate Logistic regression analysis was performed to identify independent risk factors, and a nomogram model was developed using R software. Model performance was assessed using receiver operating characteristic (ROC) curve analysis and Calibration curve. Results Univariate analysis indicated significant differences between the recurrence and non-recurrence groups in fibroid type, number, diameter, and surgical approach (P<0.05). Multivariate Logistic analysis confirmed that fibroid type, multiple fibroids, and larger fibroid diameter were independent risk factors for recurrence (P<0.05). The nomogram model incorporating these factors demonstrated good predictive performance, with an area under the ROC curve (AUC) of 0.8026, sensitivity of 0.5935, and specificity of 0.8723. The Calibration curve confirmed good agreement between predicted and actual probabilities, indicating excellent model calibration. Conclusion Fibroid type, number, and diameter are significant risk factors for postoperative recurrence. The developed nomogram model shows satisfactory predictive performance for clinical application.