The objective was to evaluate the effect of tocilizumab on the mortality indexes in patients with severe COVID-19 by using linear graph modeling and a state transition probability matrix to describe the COVID-19 course. Materials and Methods. Official statistical data on the absolute and relative numbers of COVID-19 cases were used. Linear graphs of states were used to model the COVID-19 course. Sensitivity analysis was performed to determine how the model output (the fatality rate) changes as a result of simultaneous changes in p (a transition from severe to critical disease), p (a transition from severe disease to death), and p (a transition from critical disease to death). Results. The input was a model group of 1000 patients, which were initially distributed by disease severity according to the statistical data. The model yields an absolute mortality of 54 patients; the fatality rate is 5.4% at the given state transition probabilities. Tocilizumab administration is intended only in severe and critical cases, where cytokine storm occurs. With this input, the model yields an absolute mortality of 48 patients (fatality rate is 4.8%). The probabilities in sensitive analysis were varied in a range of ±50% with an increment of 10%. Calculations showed that 10% decreases in probabilities p , p , and p decrease the fatality rate to the same extent, by 10.39%. Conclusion. A decrease in the rate of transition to critical disease reduces the fatality rate in COVID-19 to the same extent. Promising results have been obtained with tocilizumab, demonstrating a decrease in the frequency of critical cases and, therefore, the fatality rate. The safety profile and efficacy of the drug need additional verification. 34 35 45 34 35 45