Gastric cancer (
GC
) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of
GC
patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained micro
RNA
expression profiles of 385
GC
patients from The Cancer Genome Atlas. We performed Cox regression analysis to identify overall survival‐related micro
RNA
and then constructed a micro
RNA
signature‐based prognostic model. The accuracy of the model was evaluated and validated through Kaplan–Meier survival analysis and time‐dependent receiver operating characteristic (
ROC
) curve analysis. The independent prognostic value of the model was assessed by multivariate Cox regression analysis. Enrichment analysis was performed to explore potential functions of the prognostic micro
RNA
. Finally, a prognostic model based on a six‐micro
RNA
(mi
RNA
‐100, mi
RNA
‐374a, mi
RNA
‐509‐3, mi
RNA
‐668, mi
RNA
‐549, and mi
RNA
‐653) signature was developed. Further analysis in the training, test, and complete The Cancer Genome Atlas set showed the model can distinguish between high‐risk and low‐risk patients and predict 3‐year and 5‐year survival. The six‐micro
RNA
signature was also an independent prognostic marker, and enrichment analysis suggested that the micro
RNA
may be involved in cell cycle and mitosis. These results demonstrated that the model based on the six‐micro
RNA
signature can be used to accurately predict the prognosis of
GC
patients.