Background: To develop a novel prognostic model based on clinical characteristics and blood biomarkers to estimate overall survival (OS) and progression-free survival (PFS) in osteosarcoma (OSC) patients.Methods: A total of 71 patients with OSC from Sun Yat-sen University Cancer Center were retrospectively included. The novel prognostic model for predicting OS and PFS was established by using Lasso regression analysis based on blood biomarkers. The predictive accuracy and discriminative ability of the novel prognostic model was compared with TNM staging and clinical treatment using concordance index (C-index), time-dependent ROC (tdROC) curve, decision curve analysis (DCA), net reclassification improvement index (NRI), and integrated discrimination improvement index (IDI).Results: Based on the Lasso regression analysis, we identified a 5 prognostic factors module (RBC, Ca2+, CRE, PNI, and LSR) as a novel predictive model for the OSC patients. The C-index of the novel prognostic model for predicting OS and PFS were 0.782 (95% CI = 0.658 - 0.905) and 0.741 (95% CI = 0.632 - 0.851), respectively, which were higher than that of TNM staging and clinical treatment. The tdROC curve and DCA also showed the novel model had good predictive accuracy and discriminatory power than TNM staging and treatment both in predicting OS and PFS. Moreover, the novel prognostic model performed well in all time frames (1, 3 and 5 years) in terms of the IDI and NRI when compared with the TNM staging, and clinical treatment.Conclusions: The novel prognostic model showed favorable performance than TNM staging and clinical treatment for predicting OS and PFS in OSC patients.