Isolated atherosclerotic popliteal artery lesions (IAPAL) commonly require interventional treatment. This study aimed to develop a prediction model using procedure-related variables for one-year clinically driven target lesion revascularization (CDTLR) events after intervention. Clinical data were retrospectively collected from 217 patients who underwent endovascular treatment for isolated atherosclerotic popliteal artery lesions between 2017 and 2022. Based on inclusion and exclusion criteria, all patients were randomly divided into training and testing sets at a ratio of 7:3. In the training set, LASSO regression, logistic regression, and random forest were used to identify the most significant variables for outcome events. These variables were then incorporated into a multivariate logistic regression model. The prediction model was visualized using a nomogram and validated using training and testing sets. The final nomogram consisted of three independent predictors: body weight, drug-coating balloon angioplasty, and post-procedural outflow score. The regression equation was: Y = 3.65–0.0645×weight − 1.04×(DCB = use) − 1.21×(post-procedural outflow score = 2) − 0.465×(post-procedural outflow score = 3). The prediction model demonstrated C-indices of 0.756 and 0.689 in the training and validation cohorts, respectively. Calibration curves showed satisfactory agreement in both cohorts. The prediction model incorporating body weight, drug-coating balloon angioplasty, and post-procedural outflow score may assist in predicting one-year clinically driven target lesion revascularization in patients with isolated atherosclerotic popliteal artery lesions, providing valuable information for individualized treatment strategies.The online version contains supplementary material available at 10.1038/s41598-025-17283-9.