Objective: The purpose of this study was to develop and validate a nomogram that can be used to predict lymph node metastasis (LNM) in patients with endometrial carcinoma (EC). Methods: Clinical data of EC patients diagnosed between 2004 and 2015 were retrieved from the Surveillance, Epidemiology, and End Results Program (SEER) registry. The nomogram was constructed using independent risk factors chosen using a multivariate logistic regression analysis. Accuracy was validated for both groups using discrimination analysis and calibration curves. The predictive accuracy and clinical value of the nomogram and Mayo criteria were compared using decision curve analysis (DCA). Results: The final study group consisted of 63,836 women that met specific inclusion criteria. The factors that were identified in the multivariate analysis to be notable predictors of LNM were age, tumor size, histological type, cervical stromal invasion, tumor grade, and myometrial invasion. These risk factors were included in the nomogram. Discriminations of the nomogram and Mayo criteria were 0.848 (95% CI: 0.843-0.853) and 0.806 (95%CI: 0.801-0.812), respectively. In the validation group, the AUC values were 0.847 (95%CI: 0.840-0.857) and 0.804 (95%CI: 0.796-0.813) for the nomogram and the Mayo criteria, respectively ( P <0.01). Calibration plots showed that training and validation cohorts were well-calibrated. DCA revelaed that by using the nomogram always had a positive net benefit compared to using the Mayo criteria. Conclusions: A nomogram was developed to predict LNM in EC patients based on a large population-based analysis. The nomogram showed good performance for predicting LNM in patients with EC.