Background: Although pancreatic neuroendocrine tumors (PNETs) are considered indolent tumors, most patients are diagnosed at an advanced stage. We aimed to establish a nomogram for clinical use to predict the survival of PNET patients using the Surveillance, Epidemiology, and End Results (SEER) database.Methods: Based on the SEER database, 1,103 patients with PNETs were enrolled and randomly divided into training and validation sets. We performed Kaplan-Meier analysis and Cox proportional hazard regression analysis in the training set to evaluate the value of the prognostic factors. A nomogram was then constructed to analyze these independent prognostic factors for predicting the overall survival (OS) and specific cancer survival (CSS). C-index, calibration curve, and decision curve analysis were used to evaluate the predictive accuracy of the nomogram.Results: Age, primary site, TNM stage, grade, and surgery were associated with OS and CSS in the multivariate models. Nomograms were established depending on these risk factors and had a better discrimination power than the TMN stage. The validation techniques showed that the nomograms were able to predict the 3- and 5-year OS and CSS accurately, and also proved to be superior.Conclusions: Nomograms were established depending on these risk factors and had a better discrimination power than the TMN stage. The validation techniques showed that the nomograms were able to predict 3- and 5-year OS and CSS accurately, and also proved to be superior.