The study aimed to explore the influencing factors on critical coronavirus disease 2019 (COVID-19) patients' prognosis and to construct a nomogram model to predict the mortality risk . We retrospectively analyzed the demographic data and corresponding laboratory biomarkers of 102 critical COVID-19 patients with a residence time & #8805; 24 h and divided patients into survival and death groups according to their prognosis . Multiple logistic regression analysis was performed to assess risk factors for critical COVID-19 patients and a nomogram was constructed based on the screened risk factors . Logistic regression analysis showed that advanced age, high peripheral white blood cell count (WBC), low lymphocyte count (L), low platelet count (PLT), and high-sensitivity C-reactive protein (hs-CRP) were associated with critical COVID-19 patients mortality risk (p <0.05) and these were integrated into the nomogram model . Nomogram analysis showed that the total factor score ranged from 179 to 270 while the corresponding mortality risk ranged from 0.05 to 0.95 . Findings from this study suggest advanced age, high WBC, high hs-CRP, low L, and low PLT are risk factors for death in critical COVID-19 patients . The Nomogram model is helpful for timely intervention to reduce mortality in critical COVID-19 patients.