2 Background: A novel prediction model, the Yonsei University Gastric Cancer Prediction Tool was developed by an international collaborative group (G6+) for accurate determination of 5-year overall survival of gastric cancer patients. This prediction model was created using a prospectively maintained single institution database of 12,399 patients and included clinically relevant factors not accounted for in the TNM staging system. This prediction model was validated using external data sets from Asia; its’ applicability in the American population has yet to be determined through a validated data set. Methods: Using the SEER dataset, 2014 release, all patients with gastric adenocarcinoma diagnosed between the years 2002 –2012 who underwent resection were selected. The following characteristics were selected for analysis: age, sex, gender, depth of tumor invasion, number of positive lymph nodes, total lymph nodes retrieved, presence of distant metastasis, extent of resection, and histology. These data were processed through a recently published prognostic nomogram to obtain concordance index (C-statistic) using the bootstrap method and calibration was assessed. This was compared to the current prognostic index, the TNM staging system. Results: A total of 26,019 possible patients were identified from the SEER database, years 2002-2012. Of these, 11,765 had complete datasets. Validation of the prognostication model revealed a C-statistic of 0.762 (95% CI 0.754-0.769). This is compared to the 7thTNM staging model, C-statistic 0.683 (95% CI 0.677-0.689). The new nomogram was found to be significantly more accurate with a p-value of < 0.001. Conclusions: Our study validates a novel prediction model for gastric cancer in the American patient population. Using this model, superior accuracy in prognosticating the 5-year survival of gastric cancer patients was confirmed in the western cohort strongly supporting its global applicability. This model also allows for inclusion of those who did not undergo adequate lymphadenectomy or who underwent a non-curative resection and can be a useful prediction tool for an increasing number of gastric cancer patients world-wide.