Objective To establish a nomogram for predicting the distant metastasis risk of pancreatic neuroendocrine tumors (pNETs) in elderly patients.Methods We extracted data of patients with diagnosis of pNETs at age ≥65 years old between 1973 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. All eligible patients were divided randomly into a training cohort and validation cohort. Uni- and multivariate logistic regression analyses were performed on the training cohort to identify independent factors for distant metastasis. A nomogram was developed based on the independent risk factors using rms packages of R software, and was validated internally by the training cohort and externally by the validation cohort using C-index and calibration curves. Results A total of 411 elderly patients were identified, of which 260 were assigned to training cohort and 151 to validation cohort. Univariate and multivariate logistic regression analyses indicated the tumor site (body/tail of pancreas: odds ratio [OR]=2.282; 95％ confidence interval [CI]: 1.174 – 4.436, P<0.05), histological grade (poorly differentiated/undifferentiated: OR=2.600, 95％ CI: 1.266–5.339, P<0.05), T stage (T2: OR=8.913, 95％ CI: 1.985–40.010, P<0.05; T3: OR=11.830, 95％ CI: 2.530–55.350, P<0.05; T4: OR=68.650, 95％ CI: 8.020–587.600, P<0.05), and N stage (N1: OR=3.480, 95％ CI: 1.807–6.703, P<0.05) were identified as independent risk factors for distant metastasis of pNETs in elderly. The nomogram exhibited good predicting accuracy, with a C-index of 0.809 (95％ CI: 0.757 – 0.861) in internal validation and 0.795 (95％ CI: 0.723 – 0.867) in external validation, respectively. The predicted distant metastasis rates were in satisfactory agreement with the observed values by the calibration curves. Conclusion The nomogram we established showed high discriminative ability and accuracy in evaluation of distant metastasis risk in elderly pNETs patients, and could provide a reference for individualized tumor evaluation and treatment decision in elderly pNETs patients.