Objectives <p>To investigate and analyze the factors affecting postoperative urinary retention (POUR) after pelvic floor reconstruction, and to construct and validate a risk prediction model.</p> Methods <p>This retrospective cohort study included 258 pelvic floor reconstruction patients (2023–2024) from a Southwest China tertiary hospital. Patients were classified into POUR and non-POUR groups and split 7:3 into training and internal validation cohorts. Predictors were identified through univariate analysis and multivariate logistic regression analysis to construct a Nomogram model. Receiver Operating Characteristic (ROC) curves, calibration curves, and the Hosmer–Lemeshow test evaluated the model's differentiation, calibration, goodness-of-fit, and predictive performance.</p> Results <p>Independent POUR risk factors were: urinary retention history (OR = 10.008, 95% CI 1.368–73.195, <i>P</i> = 0.023), heart disease (OR = 14.416, 95% CI 2.872–72.376, <i>P</i> = 0.001), number of vaginal deliveries (OR = 1.569, 95% CI 1.076–2.289, <i>P</i> = 0.019), and maximal urinary flow rate (OR = 0.845, 95% CI 0.76–0.94, <i>P</i> = 0.002). The AUC values of the training cohort and internal validation cohort were 0.812 (95% CI 0.726–0.899) and 0.822 (95% CI 0.703–0.941), respectively. Calibration curves indicated good agreement between predicted and observed values, and the Hosmer–Lemeshow test demonstrated high predictive accuracy (<i>P</i> &gt; 0.05).</p> Conclusions <p>The nomogram model effectively predicts POUR risk, aiding early perioperative identification of high-risk patients.</p>