<p>This study aimed to develop and validate a nomogram model to predict overall survival (OS) in patients with type II endometrial carcinoma (EC). Data from patients with confirmed type II EC enrolled between 2010 and 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly allocated to training and validation groups in a 7:3 ratio. Univariable and multivariable analyses were performed to identify independent prognostic risk factors, which were included in constructing the nomogram model. The concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to assess the prediction accuracy and clinical utility of the nomogram model. The effects of different variables on survival probability were analyzed using the Kaplan-Meier method. A total of 3,933 eligible patients with type II EC were identified and included in this study. Independent risk factors for type II EC were found to be race, tumor size, histology, grade, T stage, N stage, M stage, examination of para-aortic lymph nodes, examination of pelvic lymph nodes, surgery, lung metastasis, radiation therapy, and chemotherapy. A prognostic nomogram was constructed based on these variables. The C-index for the training cohort was 0.791 (95% CI 0.780–0.802) and for the validation cohort was 0.798 (95% CI 0.778–0.818). The ROC curve demonstrated good prediction accuracy. The calibration curve indicated strong agreement between predicted and actual values. The DCA showed that the nomogram model has significant clinical utility and potential. This study developed a survival prediction model for patients with type II EC to assist clinicians in evaluating prognostic factors, predicting OS, and determining appropriate treatment protocols to improve patient outcomes.</p>