Abstract: ob＜x＞jective To construct the prognostic risk model of esophageal carcinoma (ESCA) ba＜x＞sed on the immune associated genes (IAGs) with the help of bioinformatics technology. Methods The gene ex＜x＞pression data and clinical data of ESCA were downloaded from public databa＜x＞ses to screen p rognostic related IAGs (pIAGs). The prognostic risk model was constructed ba＜x＞sed on the pIAGs and its predictive efficiency was then evaluated. Results According to the analysis results of differentially expressed genes, a total of 9 core pIAGs were identified to construct the prognostic risk model of ESCA. The prognosis of ESCA patients in the high risk group was significantly worse than those in the low risk group . The ROC curve suggested that the model had good predictive efficiency (AUC=0.833) and could be used as an independent prognostic risk factor for ESCA patients. Conclusions The prognostic risk model of ESCA ba＜x＞sed on IAGs could provide accurate prognosis assessment for ESCA patients with different clinical characteristics.