Background: Ferroptosis has been found to affect the prognosis and immunotherapy of hepatocellular carcinoma (HCC). However, the association between ferroptosis-related genes and infiltrating immune cells in tumor immune microenvironment (TIME) has not been fully elucidated. This study aimed at establishing a prediction model for the progression of HCC using ferroptosis-associated genes based on immune score. Methods: Transcriptomic, mutation and clinicopathological information were downloaded from TCGA and International Cancer Genome Consortium (ICGC) for this study. Construction of the prediction model was done by Lasso regression analysis. Estimation of the clustering ability of the prediction model was done by t-distributed stochastic neighbor embedding (t-SNE) and principal component analysis (PCA) analyses. Assessment of the accuracy of the prediction model was done by receiver operating characteristic (ROC) and Kaplan-Meier curves. Results: A prediction model was formulated utilizing three ferroptosis-related genes (G6PD, SAT1 and SLC1A5). The model independently predicted the overall survival (OS). Differentially expressed genes (DEGs) linked to based on Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analyses immune-associated pathways and functions. Single-sample gene set enrichment analysis (ssGSEA) strategy further confirmed the model was related to immune-associated functions as well as immune cell infiltration. Conclusions: The three ferroptosis-associated gene-based prediction model was good at predicting the OS outcomes of HCC, improve HCC prognostication and treatment in the clinic.