Ferroptosis has recently been associated with immunological changes in sepsis. However, the clinical significance of ferroptosis-associated genes (FAGs) remains unknown. In this paper, a FAG-based prognostic model was constructed for sepsis patients using an integrated machine learning approach. The prognosis model was composed of 14 FAGs that classify the patients as high or low risk. Based on immunological study, it was found that the immune status differed between the high-risk and low-risk clusters. Cox regression analysis revealed that FAGs were independent risk factors for the overall survival of sepsis patients. ROC curves and nomograms revealed that the FAG-based model was robust for prognosis prediction. Lastly, NEDD4L was identified from the 14 FAGs as a potential hub gene for sepsis prediction.