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This study aims to identify a miRNAs signature for predicting overall survival (OS) in esophageal squamous cell carcinoma (ESCC) patients. MiRNA expression profiles and corresponding clinical information of 119 ESCC patients were obtained from NCBI GEO and used as the training set. Differentially expressed miRNAs (DEmiRNAs) were screened between early-stage and late-stage samples. Cox regression analysis, recursive feature elimination (RFE)-support vector machine (SVM) algorithm, and LASSO Cox regression model were used to identify prognostic miRNAs and consequently build a prognostic scoring model. Moreover, promising target genes of these prognostic miRNAs were predicted followed by construction of miRNA-target gene networks. Functional relevance of predicted target genes of these prognostic miRNAs in ESCC was analyzed by performing function enrichment analyses. There were 46 DEmiRNAs between early-stage and late-stage samples in the training set. A risk score model based on five miRNAs was built. The five-miRNA risk score could classify the training set into a high-risk group and a low-risk group with significantly different OS time. Risk stratification ability of the five-miRNA risk score was successfully validated on an independent set from the Cancer Genome Atlas (TCGA). Various biological processes and pathways were identified to be related to these miRNAs, such as Wnt signaling pathway, inflammatory mediator regulation of TRP channels pathway, and estrogen signaling pathway. The present study suggests a pathological stage-related five-miRNA signature that may have clinical implications in predicting prognosis of ESCC patients. [ABSTRACT FROM AUTHOR]