Background: CL of checkpoint inhibitors has been identified as a predictive covariate of overall survival (OS) in several tumors. Determination of CL requires post-treatment samples, which negates its utility as a baseline prognostic biomarker. This study aims to identify a baseline composite cytokine signature that correlates with NIVO CL in patients with RCC using translational PK/PD analysis. Methods: Peripheral serum PK (NIVO CL) and serum biomarkers to assess PD (Myriad Rules-Based Medicine customized inflammatory cytokine panel) were analyzed from 985 patients with RCC enrolled in 3 clinical trials. CheckMate (CM) 009 (NCT01358721) and CM 025 (NCT01668784) of NIVO (n = 481) were used for model development (training dataset). CM 010 (NCT01354431) of NIVO and a cohort treated with everolimus in CM 025 were included in model application (test dataset; n = 504). PK/PD analyses were conducted using a machine learning algorithm with performance assessed by receiver operating characteristic (ROC) curve and accuracy by confusion matrix. Results: The model selected the top-10 baseline inflammatory cytokines to form a composite cytokine signature, which predicted NIVO CL (high vs low) that was significantly associated with OS (p < 0.001) across all 3 studies (training and test datasets). The same cytokine features were associated with OS of everolimus (p < 0.01), suggesting the potential prognostic nature of the composite signature. The PK/PD analysis provided a robust description of the association between selected cytokines and CL (ROC = 0.71). Identified cytokines (eg, serum C-reactive protein known to reflect immune cell modulation) have been shown individually to be associated with RCC prognosis. A multivariable approach resulting in tumor-specific composite signatures may provide more accurate prognostic value. Conclusions: The baseline composite cytokine signature could serve as a clinically useful biomarker for patients with RCC, pending further evaluation, as it may provide improved prognostic accuracy for long-term clinical outcome compared to individual cytokines.