This study systematically investigates the roles of messenger RNAs (mRNAs) and microRNAs (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 (namely DEGs) and miRNAs (namely DEMs) are identified, and survival prognosis-related biomarkers are determined through Kaplan-Meier analysis and lasso regression. Prognostic models are 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 are identified across different prognostic models, resulting in enhanced prediction accuracy with increased stratification. The literature review confirms abnormal expressions of 28 prognostic RNAs reported in experiments and 15 prognostic RNAs reported in bioinformatics studies. The study also introduces 35 novel prognostic RNAs as potential treatment targets for RCC. The mRNA+miRNA prognostic models exhibit 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.