BACKGROUND: Hepatocellular carcinoma (HCC) represents a significant global health concern with persistently high incidence and mortality rates. Immune-related long non-coding RNAs (lncRNAs) may play crucial roles in the pathogenesis and progression of HCC, yet their precise mechanisms remain incompletely elucidated. OBJECTIVE: This study aims to explore the potential roles of immune-related lncRNAs in HCC patients through systematic biological approaches, integrating clinical data with bioinformatics analysis, and to construct a COX regression model for predicting patient survival. METHODS: The HCC dataset from The Cancer Genome Atlas (TCGA) was utilized as the study cohort. Immune-related mRNA and lncRNA data were extracted and screened for their association with HCC patient survival using Weighted Gene Co-expression Network Analysis (WGCNA) algorithm and COX regression method. A COX regression model was subsequently established and validated. RESULTS: Our investigation revealed that a COX regression model comprising a group of immune-related lncRNAs and mRNAs could accurately predict patient survival in HCC. Specific analyses indicated the pivotal roles of these RNAs in the occurrence and progression of HCC, particularly in immune regulation. CONCLUSIONS: The findings of this study underscore the critical role of immune-related lncRNAs and mRNAs in the prognosis of HCC patients, suggesting their potential as prognostic factors. This discovery provides important insights into the immune modulation mechanisms of HCC, offering novel avenues and methods for personalized therapy and prognostic assessment of HCC.