Background: Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A prognostic model for predicting the individual disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established. Objective: We aimed to establish a survival nomogram for GAC patients who receive surgery and chemotherapy. Methods: We identified 5764 GAC patients who had received surgery and chemotherapy from the SEER (Surveillance, Epidemiology, and End Results) database. Approximately 80% (n=4034) of the included patients were randomly assigned to the training set, and the remaining patients (n=1729) were assigned to the external validation set. Nomogram was established by the training set and validated by the validation set. Results: Based on the results of a multivariate analysis, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined, number of positive regional lymph nodes, sex, race, grade, derived AJCC stage, summary stage, and radiotherapy status. The C-index (Harrell’s concordance index) of the model was higher than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the nomogram showed that the probability of DSS optimally corresponded to the survival rate. Integrated discrimination improvement (IDI) and categorical net reclassification improvement (NRI) showed visible improvement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively (P>0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI=0.316–0.470), 0.407 (95% CI=0.350–0.505), and 0.413 (95% CI=0.336–0.519), respectively. Decision curve analysis supported that the constructed nomogram was superior to the AJCC staging system. Conclusion: The proposed nomogram provides more-reliable DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.