BACKGROUND: Due to the complexity and heterogeneity of hepatocellular carcinoma, the existing clinical staging criterias are insufficient to accurately reflect the tumor microenvironment and predict the prognosis of HCC patients. Aggrephagy, as a type of selective autophagy, is associated with various phenotypes of malignant tumors. OBJECTIVE: This study aimed to identify and validate a prognostic model based on aggrephagy-related LncRNAs to assess the prognosis and immunotherapeutic response of HCC patients. METHODS: Based on the TCGA-LIHC cohort, aggrephagy-related LncRNAs were identified. Univariate Cox regression analysis and lasso and multivariate Cox regression were used to construct a risk-scoring system based on eight ARLs. CIBERSORT, ssGSEA, and other algorithms were used to evaluate and present the immune landscape of tumor microenvironment. RESULTS: The high-risk group had a worse overall survival (OS) than the low-risk group. Patients in the high-risk group are more likely to benefit from immunotherapy because of their high infiltration level and high immune checkpoint expression. CONCLUSION: The ARLs signature is a powerful predictor of prognosis for HCC patients, and the nomogram based on this model can help clinicians accurately determine the prognosis of HCC patients and screen for specific subgroups of patients who are more sensitive to immunotherapy and chemotherapy.