Background and Aims Hepatocellular carcinoma (HCC) is currently responsible for one of the leading causes of cancer death worldwide. Accumulating evidence demonstrated that long noncoding RNAs (lncRNAs) can be used as biomarkers of tumor prognosis. However, the relationship between lncRNAs and the survival prognosis of HCC remains unclear. This study was conducted to screen the immune-related lncRNAs associated with the prognosis of HCC, and then construct a prognostic risk model.Methods The transcriptome data and clinical data of HCC were obtained from the Cancer Genome Atlas (TCGA), and the immune-related lncRNAs were extracted. The prognostic immune-related lncRNAs were screened by univariate Cox regression analysis, and were further incorporated into multivariate Cox regression analysis. A prognostic risk model was established using the lncRNAs determined by the optimal AIC value, by which the patient's risk scores were calculated. The patients were divided into low-risk group and high-risk group according to the median risk value. Survival analysis of the two groups of patients was performed and their survival curves were drawn by Kaplan-Meier method. The efficiency of the prognostic risk model was assessed by drawing ROC curve. The associations of clinicopathologic variables and risk score with the overall survival of the patients were determined by univariate and multivariate Cox regression analysis.Results A total of 143 immune-related lncRNAs were extracted from HCC (Cor>0.6, P<0.001). Seventeen prognostic immune-prognostic-related lncRNAs were screened by univariate Cox regression analysis, and 8 of them (AL139384.1, MAPKAPK5-AS1, LINC02362, SLC25A30-AS1, DANCR, AC124798.1, LINC02499 and AC023157.3) were obtained after incorporation into multivariate Cox regression analysis to establish a prognostic risk model. The survival rate of patients in low-risk group was significantly higher than that of patients in high-risk group (P<0.05). The area under the ROC curve of the prognostic risk model was 0.774, and the multivariate Cox regression analysis showed that the risk score was an independent factor influencing the prognosis of HCC patients (HR=1.608, 95% CI=1.351-1.913, P<0.001).Conclusion The establishment of prognostic risk model based on 8 immune-related lncRNAs can effectively predict the survival prognosis of HCC patients, and the risk score is an independent prognostic factor for HCC.