This study systematically investigates the role of mRNAs and miRNAs in renal cell carcinoma (RCC) and their potential as diagnostic and prognostic biomarkers via a stratification approach. By utilizing the Cancer Genome Atlas (TCGA) database, differentially expressed mRNAs (DEGs) and miRNAs (DEMs) were identified, and survival prognosis-related biomarkers were determined through Kaplan-Meier analysis and lasso regression. Prognostic models were established for RCC ethnicity, pathologic stages, and metastatic status, with validation through plotting risk heatmaps, risk curves, survival curves, and receiver operating characteristic (ROC) curves. A total of 45 mRNA and 33 miRNA biomarkers were identified across different prognostic models, resulting in enhanced prediction accuracy with increased stratification. The literature review confirms abnormal expressions of 28 and 15 prognostic RNAs, reported respectively in experimental and bioinformatics studies. The study also introduced 35 novel prognostic RNAs as potential treatment targets for RCC. The mRNA+miRNA prognostic models exhibited the most robust predictive capability, indicating their potential clinical relevance. Overall, the study contributes to a precise prognosis of RCC by exploring novel biomarkers and potential therapeutic targets.