The study focused on cesarean scar pregnancy (CSP), a rare but increasingly common form of ectopic pregnancy associated with serious postoperative complications. The authors retrospectively analyzed 917 patients with CSP from December 2015 to March 2024, who were randomly divided into a training (n = 689) and a validation cohort (n = 228). Using multivariate logistic regression, they identified four independent risk factors for postoperative complications: gestational age, interval since the last caesarean section, residual myometrial thickness in the scar area, and intraoperative blood loss. Based on these variables, they created a nomogram model to predict the risk of complications after CSP surgery. The model had very good discriminative power, with the area under the ROC curve (AUC) being 0.868 in the training and 0.865 in the validation cohort. The calibration plots showed a good agreement between the predicted and the actual observed risk of complications. Analysis of the decision curve and clinical impact confirmed that the nomogram has practical clinical utility in assessing the risk of postoperative complications in patients with CSP.