The pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently being studied, which makes it difficult to make an accurate prognosis. This research was conducted to determine whether certain hematological indicators may be used to forecast the severity and mortality of coronavirus disease (COVID-19). A total of 240 patients with COVID-19 were retrospectively analyzed in this study. Researchers compared the hematological parameters across severity levels. To analyze the data, they employed the receiver operating characteristics (ROC) curve and the Classification and Regression Trees (CART) methods. While the absolute lymphocyte count and the lymphocyte-monocyte ratio (LMR) were falling (P<0.001), the total leukocyte count, absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), and neutrophil-monocyte ratio (NMR) were all increasing as the severity of the infection worsened. The NLR, NMR, and lymphocyte-monocyte ratio (LMR) were all statistically significant (P<0.001) for predicting severity and mortality on admission. Depending on the level of severity, the area under the receiver operating characteristics curve (AUROC) for the NLR, NMR, and LMR was 0.86 (95% CI, 0.80-0.91), 0.822 (95% CI, 0.76-0.88), and 0.69 (95% CI, 0.60-0.79), respectively. While the AUROC for mortality prediction was 0.85 (95% CI 0.79-0.92), 0.83 (95% CI 0.77-0.89), and 0.67 (95% CI 0.57-0.78) for the NLR, NMR, and LMR, respectively. Total leukocyte count and absolute neutrophil count both rose as severity increased, whereas absolute lymphocyte count fell. It is possible to forecast the severity and mortality of COVID-19 at the time of admission if the patient’s NLR is greater than 5.2, NMR is greater than 12.1, and LMR is less than 2.4.