BACKGROUND: Liver resection is the most effective treatment for intrahepatic cholangiocarcinoma. Recurrent disease is frequent; however, recurrence patterns are ill-defined and prognostic models are lacking. STUDY DESIGN: A primary cohort of 189 patients who underwent resection for intrahepatic cholangiocarcinoma was used for recurrence patterns analysis within and after 24 months. Based on independent factors for disease-free survival identified in Cox regression analysis, preoperative and postoperative models were developed using a recursive partitioning method. Models were externally validated using a multicenter cohort of 522 resected patients (Association Française de Chirurgie intrahepatic cholangiocarcinoma study group). RESULTS: Recurrence within 24 months most often involved the liver (82.7%), and most recurrences after 24 months were strictly extrahepatic (61.1%). In multivariable analysis of the primary cohort, independent preoperative factors for disease-free survival were tumor size and multifocality (based on imaging); tumor size, multifocality, vascular invasion, and lymph node metastases (based on pathology) were independent postoperative factors. The preoperative model allowed patient classification into low-risk and high-risk groups for recurrence. In the validation cohort (n = 522), high-risk patients had a greater likelihood of recurrence (hazard ratio = 2.17; 95% CI, 1.74-2.72; p < 0.001). The postoperative model included tumor size, vascular invasion, and positive nodal disease on pathology and classified patients in low-, intermediate-, and high-risk groups in the primary cohort. As compared with low-risk patients in the validation cohort, intermediate- and high-risk patients were more likely to experience recurrence (hazard ratio = 1.9; 95% CI, 1.41-2.47; p < 0.001 and hazard ratio = 2.99; 95% CI, 2.08-4.31; p < 0.001, respectively). CONCLUSIONS: Recurrence patterns are time dependent. Both models as developed and validated in this study classified patients in distinct recurrence risk groups, which can guide treatment recommendations.