Background: Gastric cancer is the fifth most common cancer and the third top cause of cancer related death withabout 1 million new cases and 700,000 deaths in 2012. The aim of this investigation was to identify important factors foroutcome using a random survival forest (RSF) approach. Materials and Methods: Data were collected from 128 gastriccancer patients through a historical cohort study in Hamedan-Iran from 2007 to 2013. The event under consideration wasdeath due to gastric cancer. The random survival forest model in R software was applied to determine the key factorsaffecting survival. Four split criteria were used to determine importance of the variables in the model including log-rank,conversation?? of events, log-rank score, and randomization. Efficiency of the model was... confirmed in terms of Harrell’sconcordance index. Results: The mean age of diagnosis was 63 ±12.57 and mean and median survival times were 15.2(95%CI: 13.3, 17.0) and 12.3 (95%CI: 11.0, 13.4) months, respectively. The one-year, two-year, and three-year ratesfor survival were 51%, 13%, and 5%, respectively. Each RSF approach showed a slightly different ranking order. Veryimportant covariates in nearly all the 4 RSF approaches were metastatic status, age at diagnosis and tumor size. Theperformance of each RSF approach was in the range of 0.29-0.32 and the best error rate was obtained by the log-ranksplitting rule; second, third, and fourth ranks were log-rank score, conservation of events, and the random splittingrule, respectively. Conclusion: Low survival rate of gastric cancer patients is an indication of absence of a screeningprogram for early diagnosis of the disease. Timely diagnosis in early phases increases survival and decreases mortality.