Background: Coronavirus disease 2019 (COVID-19) has resulted in an overwhelmed challenge to the healthcare system worldwide. Methods: A case-control study of COVID-19 patients in Wuhan Third Hospital was conducted. 96 deceased COVID-19 patients and 230 discharged patients were included as the case group and control group, respectively. Demographic, epidemiological, clinical and laboratory variables on admission were collected from electronic medical records. Univariate and multivariate logistic regression were adopted to investigate the independent predictors of mortality. A nomogram was formed for predicting the mortality risk. Results: The multivariate stepwise logistic model demonstrated that age of 60+ years (OR =4.426, 95% CI: 1.955-10.019), comorbidity of cerebrovascular disease (OR =7.084, 95% CI: 1.545-32.471), white blood cell (WBC) count >9.5x10(9)/L (OR =7.308, 95% CI: 1.650-32.358), platelet count <125x10(9)/L (OR =5.128, 95% CI: 2.157-12.191), aspartate aminotransferase (AST) >40 U/L (OR =2.554, 95% CI: 1.253-5.206), cystatin C >1.1 mg/L (OR =4.132, 95% CI: 2.118-8.059), C reactive protein (CRP) =100 mg/L (OR =2.830, 95% CI: 1.311-6.109), creatine kinase isoenzymes (CK-MB) >24 U/L (OR =6.015, 95% CI: 2.119-17.07) and D-dimer >5 mu g/L (OR =4.917, 95% CI: 1.619-14.933) were independent predictors of mortality of COVID-19 patients. The nomogram demonstrated a well discriminatory accuracy for mortality prediction with a C-index of 0.903. Conclusions: The determinants identified may help to determine patients at high risk of death at an early stage and guide the optimal treatment.