Objective:To construct a mortality prediction model for severe fever with thrombocytopenia syndrome (SFTS) and to evaluate its prediction ability.Methods:Clinical data of 120 hospitalized patients with SFTS at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from January 2017 to June 2023 were retrospective analyzed. Based on clinical prognosis, patients were divided into survival group ( n=89) and fatal group ( n=31). The risk factors of SFTS mortality were analyzed with multivariate Logistic regression, based on which a mortality risk prediction model was constructed. The predictive value of the model was examined with receiver operator characteristic (ROC) curve. SPSS 23.0 software was used to process and analyze the data. Results:Logistic regression analysis indicated that skin petechiae ( OR=5.171, 95% CI 1.617-16.530, P=0.006), mental disturbance ( OR=5.481, 95% CI 1.540-19.512, P=0.009), increased serum lactate dehydrogenase level ( OR=1.002, 95% CI 1.001-1.004, P<0.001), and increased serum creatinine level ( OR=1.018, 95% CI: 1.007-1.029, P=0.002) were independent risk factors for SFTS mortality. A mortality risk prediction model was established based on the regression coefficient of risk factors: Logit( P)=-6.623+ skin petechiae×1.643+ mental disturbance × 1.701+ lactate dehydrogenase level (U/L)×0.002+ creatinine level (μmol/L)×0.018. The area under ROC curve (AUC) of the prediction model was 0.91 (95% CI 0.86-0.96, P<0.001), and its predictive ability was higher than that of skin petechiae ( Z=3.788, P<0.001), mind change ( Z=5.728, P<0.001), lactate dehydrogenase ( Z=2.309, P=0.021), and creatinine ( Z=2.064, P=0.039). Conclusion:The mortality prediction model constructed based on skin petechiae, mental disturbance, lactate dehydrogenase, and creatinine has good predictive value for the prognosis of SFTS patients.