Abstract: Objective: To construct a joint-model column chart based on the radiomic features of multi-slice spiral computed tomography (MDCT) and abdominal fat area parameters of gastric adenocarcinoma to predict occult peritoneal metastasis (OPM) in patients with advanced gastric adenocarcinoma. Method: 121 patients with advanced gastric adenocarcinoma confirmed by pathology to have OPM and 85 patients without OPM were randomly divided into a training group (n=145) and a validation group (n=61) in a 7︰3 ratio. First, primary gastric cancer tumor was selected as the region of interest on the arterial-phase abdominal MDCT image to extract radiomic features. Second, the visceral fat area (VFA) and subcutaneous fat area (SFA) were measured at the third lumbar spine level based on the abdominal MDCT images. A joint model was constructed by combining radiomic features and abdominal fat area parameters closely related to the OPM, and a column chart was plotted. Finally, the predictive performance of the model was evaluated using receiver operating characteristic curve, decision curve, and calibration curve methods. Results: Six core radiomic features were identified, and VFA and SFA were found to be closely associated with the OPM occurrence in gastric adenocarcinoma. In both the training and validation groups, the combined imaging omic–fat-area-parameter model (AUC, 0.899 and 0.876) outperformed the imaging omic (AUC, 0.838 and 0.776) and fat area models alone (AUC, 0.824 and 0.751) in predicting the OPM occurrence in patients with advanced gastric cancer, and the differences were statistically significant. Decision curve analysis showed that within most threshold ranges, the predictive performance of the joint model was superior to the individual predictive performances of the radiomic and abdominal fat models, demonstrating better clinical practicality of the joint model. Conclusion: A combined model of MDCT radiomic features and abdominal fat area parameters of gastric adenocarcinoma can effectively predict OPM occurrence in advanced gastric adenocarcinoma.