©　2018　Elsevier　GmbH　Object:　This　study　focused　on　the　identification　of　prognostic　miRNAs　for　the　prediction　of　tumor　recurrence　and　progress　in　esophageal　cancer.　Methods:　MiRNA　profiling　and　clinical　characteristics　of　esophageal　cancer　patients　was　downloaded　from　the　TCGA　database.　Univariate　analysis　was　performed　to　select　potential　prognostic　miRNAs　and　covariates.　LASSO　based　logistic　regression　was　conducted　to　identify　the　prognostic　miRNAs　given　covariates.　Bioinformatics　analysis　including　gene　ontology,　disease　ontology　and　pathway　enrichment　analysis　were　performed.　A　nomogram　was　generated　based　on　multivariate　logistic　regression　to　illustrate　the　association　between　the　identified　miRNAs　and　the　risk　of　tumor　recurrence　and　progress.　Results:　A　total　of　1881　miRNAs　and　10　clinical　characteristics　were　obtained　from　TCGA　database.　18　miRNAs　were　finally　identified　in　which　6　miRNAs　were　identified　for　the　first　time　to　be　associated　with　the　tumor　recurrence　and　progress　of　esophageal　cancer　given　covariates.　Bioinformatics　analysis　suggested　that　the　identified　miRNAs　were　associated　with　the　tumor　recurrence　and　progress　of　esophageal　cancer.　The　association　between　identified　miRNAs　and　risk　of　tumor　recurrence　and　progress　were　presented　in　a　nomogram.　Conclusion:　The　6　newly　identified　miRNAs　may　be　potential　biomarkers　for　the　prediction　of　tumor　recurrence　and　progress　of　esophageal　cancer.