Osteosarcoma, a primary malignant bone tumor predominantly affecting children and adolescents, is characterized by aerobic glycolysis, which is intricately linked to tumor progression and metastasis, yet its prognostic implications remain underexplored. This study aimed to develop a prognostic model utilizing glycolysis-related genes and to elucidate the functional role of P4HA1, a key gene within this model, in osteosarcoma prognosis and immune cell infiltration. We collected clinical and transcriptomic data from osteosarcoma patients in the UCSC Xena and GEO databases. Through univariate Cox and LASSO regression analyses, we identified 12 glycolysis-related genes that significantly influence osteosarcoma prognosis. These genes were employed to construct a risk score model, which accurately predicted patient outcomes as demonstrated by survival analysis and ROC curves, with an AUC of 0.899, 0.881, and 0.878 for 1-year, 3-year, and 5-year survival predictions, respectively. The model was particularly effective across different clinical subgroups. Immune cell infiltration analysis revealed that CD8