Background/Objectives: The study was aimed to determine the value of the modified Brixia score (MBS) in predicting in-hospital mortality and acute respiratory distress syndrome (ARDS) in hospitalized COVID-19 patients. Methods: We conducted an observational retrospective study including 292 COVID-19 patients (61% males, median age 74 years, interquartile range 63–82) admitted to our institution from 2 February 2020 to 31 December 2021. Patients with ARDS were diagnosed according to the Berlin criteria. To determine MBS, each lung on initial chest X-ray images was divided into three zones, and for each zone, a numerical value between 0 and 3 was assigned (maximum value 18). Binary logistic regression was used to identify the best-predicting models for ARDS development and fatal outcomes. Results: MBS was higher in patients with ARDS than in patients without ARDS (median MBS 12 (interquartile range (IQR) 9–18) vs. 8 (IQR 6–11), respectively). Patients with fatal outcomes had significantly higher MBSs than surviving patients (median MBS 12 (IQR 9–16) vs. 6 (IQR 5–9), respectively). The best model that classified ARDS patients incorporated MBS, lactate dehydrogenase levels on admission, and obesity (accuracy 74.7%, sensitivity 73.1%, specificity 75.9%, area under the curve (AUC) 0.74 (95% confidence interval (CI) 0.68–0.79)). The best model that classified patients with fatal outcomes incorporated MBS, obesity, oxygen saturation, and percentage of lymphocytes on admission (accuracy 80.5%, sensitivity 78.4%, specificity 82.6%, AUC 0.86 (95% CI 0.81–0.91)). Conclusions: MBS could have an important role in predicting ARDS and mortality and stratifying patients with COVID-19 pneumonia, aiding in clinical decision-making.