Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer, with limited treatment options. In this study, we investigated the role of immune cell infiltration in PDAC progression and constructed an immune-related predictive model for patients with PDAC based on the International Cancer Genome Consortium (ICGC) cohort. Related algorithms have been used to assess the immune microenvironment. Least Absolute Shrinkage and Selection Operator (LASSO) Cox analysis was used to construct the model, and receiver operating characteristic and decision curve analysis analyses were conducted to evaluate its diagnostic and prognostic efficacy. The results demonstrated a correlation between high immune infiltration and better prognosis in PDAC. The immune-related prognostic model (IPM) identified four genes through LASSO Cox analysis, with the high IPM group being associated with a worse prognosis. Cox regression analysis confirmed that IPM is an independent risk factor for PDAC. Validation through analysis of The Cancer Genome Atlas cohort and our own individual tumor samples revealed a similar trend to that observed in the ICGC cohort. Finally, a nomogram incorporating age and IPM demonstrated efficacy in the prognostic evaluation of patients with PDAC. In conclusion, we developed a novel immune-related prognosis prediction model for PDAC that offers new possibilities for the measurement of immunotherapy and prognostic assessment of patients.