BACKGROUND & AIMS: No reliable method for evaluating intestinal fibrosis in Crohn's disease (CD) exists; therefore, we developed a computed-tomography enterography (CTE)-based radiomic model (RM) for characterizing intestinal fibrosis in CD. METHODS: This retrospective multicenter study included 167 CD patients with 212 bowel lesions (training, 98 lesions; test, 114 lesions) who underwent preoperative CTE and bowel resection at 1 of the 3 tertiary referral centers from January 2014 through June 2020. Bowel fibrosis was histologically classified as none-mild or moderate-severe. In the training cohort, 1454 radiomic features were extracted from venous-phase CTE and a machine learning-based RM was developed based on the reproducible features using logistic regression. The RM was validated in an independent external test cohort recruited from 3 centers. The diagnostic performance of RM was compared with 2 radiologists' visual interpretation of CTE using receiver operating characteristic (ROC) curve analysis. RESULTS: In the training cohort, the area under the ROC curve (AUC) of RM for distinguishing moderate-severe from none-mild intestinal fibrosis was 0.888 (95% confidence interval [CI], 0.818-0.957). In the test cohort, the RM showed robust performance across 3 centers with an AUC of 0.816 (95% CI, 0.706-0.926), 0.724 (95% CI, 0.526-0.923), and 0.750 (95% CI, 0.560-0.940), respectively. Moreover, the RM was more accurate than visual interpretations by either radiologist (radiologist 1, AUC = 0.554; radiologist 2, AUC = 0.598; both, P < .001) in the test cohort. Decision curve analysis showed that the RM provided a better net benefit to predicting intestinal fibrosis than the radiologists. CONCLUSIONS: A CTE-based RM allows for accurate characterization of intestinal fibrosis in CD.