Objective：To develop two combined clinical-radiomics models of pericoronary adipose tissue (PCAT) for the presence and characterization of non-calcified plaques on non-contrast CT scan. Approach：Altogether, 431 patients undergoing Coronary Computed Tomography Angiography (CCTA) from March 2019 to June 2021 who had complete data were enrolled, including 173 patients with non-calcified plaques of the right coronary artery(RCA) and 258 with no abnormality. PCAT was segmented around the proximal RCA on non-contrast CT scan (calcium score acquisition). Two best models were established by screening features and classifiers respectively using FeAture Explorer software. Model 1 distinguished normal coronary arteries from those with non-calcified plaques, and model 2 distinguished vulnerable plaques in non-calcified plaques. Performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC). Main results: 4 and 9 features were selected for the establishment of the radiomics model respectively through Model 1 and 2. In the test group, the AUC values, sensitivity, specificity and accuracy were 0.833, 78.3%, 80.8%, 76.6% and 0.7467, 75.0%, 77.8%, 73.5%, respectively. The combined model including radiomics features and independent clinical factors yielded an AUC, sensitivity, specificity and accuracy of 0.896, 81.4%, 86.5%, 77.9% for model 1 and 0.752, 75.0%, 77.8%, 73.5% for model 2. Significance：The combined clinical-radiomics models based on non-contrast CT images of PCAT had good diagnostic efficacy for non‑calcified and vulnerable plaques.