Background Over the past three years, COVID-19 has been a major source of mortality in intensive care units around the world. Many scoring systems have been developed to estimate mortality in critically ill patients. Our intent with this study was to compare the efficacy of these systems when applied to COVID-19. Methods The was a multicenter, retrospective cohort study of critically ill patients with COVID-19 admitted to 16 hospitals in Texas from February 2020 to March 2022. The Simplified Acute Physiology Score (SAPS) II, Acute Physiology and Chronic Health Evaluation (APACHE) II, Sequential Organ Failure Assessment (SOFA) score, and 4C Mortality scores were calculated on the initial day of ICU admission. Primary endpoints were all-cause mortality, ICU length of stay, and hospital length of stay. Results Initially, 62,881 patient encounters were assessed, and the cohort of 292 was selected based on the inclusion of the requisite values for each of the scoring systems. The median age was 56 +/- 14.93 years and 61% of patients were male. Mortality was defined as patients who expired or were discharged to hospice and was 78%. The different scoring systems were compared using logistic regression, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) analysis to compare the accuracy of prediction of the mortality and length of stay. The multivariate analysis showed that SOFA, APACHE II, SAPS II, and 4C scores were all significant predictors of mortality. The SOFA score had the highest AUC, though the confidence intervals for all of the models overlap therefore one model could not be considered superior to any of the others. Linear regression was performed to evaluate the models' ability to predict ICU and hospital length of stay, and none of the tested systems were found to be significant predictors of length of stay. Conclusion The SOFA, APACHE II, ISARIC 4-C, and SAPS II scores all accurately predicted mortality in critically ill patients with COVID-19. The SOFA score trended to perform the best.