<h4>Background</h4>Programmed cell death 1 (PD-1) or PD-ligand 1 (PD-L1) blocker-based strategies have improved the survival outcomes of clear cell renal cell carcinomas (ccRCCs) in recent years, but only a small number of patients have benefited from them.<h4>Methods</h4>In this study, we developed a multi-omics machine learning model based on inflammatory and immune signatures (TIs) to predict the response and survival of ccRCC patients to immune checkpoint blockade (ICB) therapy. This evidence concerns the gene PDCD1 and nonpapillary renal cell carcinoma.