Given the resistance to conventional treatments and limitations of immune checkpoint blockade therapy in hepatocellular carcinoma (HCC), it is imperative to explore novel prognostic models and biomarkers. The dependence of cancer cell on exogenous methionine, known as Hoffman effect, is a hallmark of HCC, with numerous studies reporting a strong correlation between methionine metabolism and tumor development. Betaine-homocysteine S-methyltransferase (BHMT), a critical component of methionine metabolism pathway, has polymorphisms linking to poor prognosis in multiple cancers. Nevertheless, there is little literature regarding the relationship between methionine metabolism and incidence, mortality of HCC, as well as the function of BHMT in HCC progression. In this study, by analyzing multiple datasets, we constructed a methionine metabolism-related prognostic model and thoroughly investigated the influence of BHMT on the prognosis of HCC. Bioinformatics analysis revealed a marked decrease in BHMT expression in HCC, which was linked to adverse clinical outcomes. CIBERSORT results suggest that BHMT promotes infiltration of M1 macrophages. Our results suggest its potential as an ideal prognostic biomarker for anti PD-L1 immunotherapy. In summary, this study innovatively provides first methionine metabolism-related prognostic model and unveils the tumor suppressive function of BHMT in HCC, providing potential mechanism by which BHMT exert its function.