Objective To investigate the feasibility of a radiomics model in the diagnosis of acute appendicitis based on abdominal plain computed tomography（CT） scan. Methods A retrospective analysis was performed for the preoperative abdominal CT imaging data and clinical data of 210 patients with acute appendicitis confirmed by surgery in our hospital from May 2015 to August 2021，and 210 patients who underwent abdominal plain CT scan due to other acute abdominal diseases during the same period of time were enrolled for the training of the radiomics model. CT scan data of the 420 patients were collected from 4 different CT devices，and the region of the appendix was manually annotated by two radiologists. The data were randomly divided into training set and test set at a ratio of 7∶3. After 102 types of image features were extracted，the Pearson correlation analysis was used for feature dimension reduction，and the recursive feature elimination method was used to select 20 most relevant features for the training and binary classification of support vector machine（SVM） to obtain a radiomics model. After the radiomics model was obtained，the test set was used to predict the results，and the receiver operating characteristic（ROC） curve was used to evaluate the performance of the radiomics model. Results After feature dimension reduction and feature selection，3 shape-based features，3 first-order features，and 14 texture features were used to train the SVM model. In the test set，the SVM model had correct prediction in 114 cases（60 appendicitis cases and 54 non-appendicitis cases） and wrong prediction in 12 cases（3 appendicitis cases and 9 non-appendicitis cases），with a sensitivity of 95.2%，a specificity of 85.7%，an accuracy of 90.5%，and an area under the ROC curve of 0.931（95%CI： 0.887-0.976）. Conclusion The radiomics model based on abdominal plain CT scan images can be used for the prediction of acute appendicitis and is expected to be used to optimize the workflow of CT examination for acute abdominal disease in the future.