Colon cancer (CC) is one of the most common gastrointestinal malignant tumors with a high mortality rate. Glycolysis is an important pathway for tumors to obtain energy. However, its role in CC remains largely unknown. In present study, we analyzed glycolysis-related gene expression to depict clinical characteristics and its relationship with tumor immunity in CC to find potential target treatments. A prognostic model based on 13 glycolysis-related genes was established by univariate and multivariate Cox regression analyses. The efficacy of the gene model was tested via survival analysis, receiver operating characteristic analysis, and principal component analysis. Furthermore, our findings revealed and validated 13 glycolysis-related genes (NUP107, SEC13, ALDH7A1, ALG1, CHPF, FAM162A, FBP2, GALK1, IDH1, TGFA, VLDLR, XYLT2, and OGDHL), which constituted a prognostic prediction model. The model exhibited clinical implication potential, had a relatively high accuracy, and was closely associated with the patients’ clinical features. In particular, the tumor stage could be clearly distinguished by glycolysis-related gene signatures. Finally, a significant difference between glycolysis-related gene colon cancer immunity and sensitive immune drugs was observed. Our glycolysis-related gene model could provide the basis for potential early individualized treatment. The 13 glycolysis-related gene signature was a reliable predictive tool for the prognosis of colon cancer. Our findings could help patients select targets for individualized treatment and immunotherapy strategies. The study findings advance our understanding of the potential mechanism of glycolysis in colon cancer.