We sought to determine neutrophil extracellular trap (NET)-related genes' potential value in improving the efficacy of diagnosis and identifying novel therapeutic targets for osteosarcoma. Data were obtained from TARGET, GEO, and CCLE database. Differentially expressed genes were identified between the subtypes based on NET-related genes. PPI network was constructed using STRING, following by ClueGO enrichment analysis. Infiltration of immune cells was calculated by ssGSEA. Risk Score model was built by LASSO Cox regression analysis. Western blot and qRT-PCR were applied to validate the expression of genes used in the model. We identified 19 NET-related genes with prognostic potential in osteosarcoma using univariate Cox regression analysis. Patients from TARGET were clustered into two subtypes with distinct prognosis and immune features. 381 DEGs were identified between the two NET subtypes. Risk Score based on BST1, SELPLG, FPR1 and TNFRSF10C was reliable to predict the prognosis of osteosarcoma patients. The four genes expressed significantly lower in osteosarcoma than normal cells. Low Risk Score individuals only existed in C1 subtype with better prognosis. Osteosarcoma were clustered into two subtypes based on NET-related genes. Risk Score model constructed by four NET-related gene was able to independently predict the prognosis of osteosarcoma.