This study aims to build a prognostic model based on lactic acid metabolism-related genes (LMRGs) to predict survival outcomes and tumor microenvironment status of Hepatocellular carcinoma (HCC) patients. The model was used to calculate riskscores of clinical samples. Survival analysis and Cox regression analysis were conducted to verify the independence and reliability of the riskscore to determine its clinical significance in prognosis evaluation of HCC. Additionally, we conducted a comprehensive analysis of tumor mutation burden (TMB), immune cell infiltration, and gene set molecular function in the high- and low-risk groups. We obtained 134 LMRGs mainly involved in cellular calcium homeostasis and calcium signaling pathways. The LMRGs in the risk assessment model included PFKFB4, SLC16A3, ADRA2B, SLC22A1, QRFPR, and PROK1. This study discovered much shorter overall survival and median survival time of patients with higher riskscores when compared to those with lower riskscores. It was indicated that for independent prediction of patients' prognosis, the riskscore had a significant clinical value. A remarkable difference was also found regarding TMB between the two groups. Finally, cell experiments demonstrated that the knockout of PFKFB4 and SLC16A3 genes suppressed lactate. Our research demonstrated that the riskscore, established based on LMRGs, is a promising biomarker.