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Objective: To develop and validate predictive models based on Ki-67 index, radiomics and Ki-67 index combined with radiomics for survival analysis of patients with clear cell renal cell carcinoma. Methods: This study enrolled 148 patients who were pathologically diagnosed as ccRCC between March 2010 and December 2018 at our institute. All tissue sections were collected and immunohistochemical staining was performed to calculate Ki-67 index. All patients were randomly divided into the training and validation sets in a 7:3 ratio.Regions of interests (ROIs) were segmented manually. Radiomics features were selected from ROIs in unenhanced, corticomedullary, and nephrographic phases. Multivariate Cox models based on the Ki-67 index and radiomics and univariate Cox models based on the Ki-67 index or radiomics alone were built, the predictive power were evaluated by the concordance (C)-index, integrated area under the curve, and integrated Brier Score. Results: Five features were selected to establish the prediction models of radiomics and combined model. The C-indexes of Ki-67 index model, radiomics model and combined model were 0.741, 0.718 and 0.782 for disease-free survival (DFS); 0.941, 0.866 and 0.963 for overall survival, respectively. The predictive power of combined model was the best in both training and validation sets. Conclusion: The survival prediction performance of combined model was better than Ki-67 model or radiomics model. The combined model is a promising tool for predicting the prognosis of patients with ccRCC in the future. Advances in knowledge: Both Ki-67 and radiomics have showed giant potential in prognosis prediction. There are few studies investigate the predictive ability of Ki-67 combined with radiomics. This study intended to build a combined model and provide a reliable prognosis for ccRCC in clinical practice.