Objective Due to the poor prognosis of colon adenocarcinoma (COAD) patients, it is necessary to screen prognosis-related genes in COAD and establish a new prognostic risk assessment model. Methods COAD-related data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were used as the training set and the validation set, respectively. Weighted gene co-expression network analysis (WGCNA)， Cox regression model and Least Absolute Selection and Shrinkage Operator (LASSO) regression analysis were used to screen prognosis-related genes of COAD and construct a prognostic model. Receiver Operating Characteristic (ROC) curve was combined with survival curve to verify the accuracy of the model, and a nomogram was established. The patients were divided into two groups according to the median value of risk score. The immune cell proportion score (IPS) was used to evaluate the immunotherapy response of the two groups. Results A total of 15 feature genes were screened. The area under the ROC curve (AUC) in the predictive model of COAD patients was >0.6, and the survival rate of high-risk group was significantly lower than that of low-risk group (P<0.05, suggesting good distinguishing ability for high- and low-risk COAD patients. Patients in the low-risk group had a higher IPS (P=0.026), indicating a better response to immunotherapy. Conclusions The model developed for COAD in this study has a good ability to predict the survival of people at high and low risk of COAD.