To identify a robust panel of microRNA (miRNA) signatures that can distinguish renal cell carcinoma (RCC) from normal kidney using miRNA expression levels. We performed a comprehensive metaanalysis of 29 published studies that compared the miRNA expression profiles of RCC tissues and adjacent normal tissues (NT) to determine candidate miRNAs as prognostic biomarkers for RCC. Using vote-counting strategy and robust rank aggregation method, we identified a statistically significant miRNA meta-signature of two upregulated (miR-21, miR-210) and three downregulated (miR-141, miR-200c and miR-429) miRNAs. X-tile plot was used to generate the optimum cut-off point for the 15 different deregulated miRNAs and Kaplan-Meier method was used to calculate CSS. In a cohort of 45 patients, the high expression of miR-21 (HR: 5.46, 95%CI: 2.02-53.39) and miR-210 (HR: 6.85, 95%CI: 2.13-43.36), the low expression of miR-141 (HR: 0.16, 95%CI: 0.004-0.18), miR-200c (HR: 0.08, 95%CI: 0.01-0.43) and miR-429 (HR: 0.18, 95%CI: 0.02-0.50) were associated with poor cancer-specific survival (CSS) following RCC resection. We also constructed a five-miRNAs-based classifier as a reliable prognostic and predictive tool for CSS in patients with RCC, especially in clear cell RCC (ccRCC) (HR: 5.46, 95% CI: 1.51-19.66). This method might facilitate patient counselling and individualise management of RCC.