AbstractThe current tumor‐node‐metastasis staging system does not provide sufficient prognostic prediction or adjuvant chemotherapy benefit information for stage II‐III colon cancer (CC) patients. Collagen in the tumor microenvironment affects the biological behaviors and chemotherapy response of cancer cells. Hence, in this study, we proposed a collagen deep learning (collagenDL) classifier based on the 50‐layer residual network model for predicting disease‐free survival (DFS) and overall survival (OS). The collagenDLclassifier was significantly associated with DFS and OS (P< 0.001). The collagenDLnomogram, integrating the collagenDLclassifier and three clinicopathologic predictors, improved the prediction performance, which showed satisfactory discrimination and calibration. These results were independently validated in the internal and external validation cohorts. In addition, high‐risk stage II and III CC patients with high‐collagenDLclassifier, rather than low‐collagenDLclassifier, exhibited a favorable response to adjuvant chemotherapy. In conclusion, the collagenDLclassifier could predict prognosis and adjuvant chemotherapy benefits in stage II‐III CC patients.