Background/Objectives: The study aimed to investigate the significance of laboratory biomarkers, particularly the lactate-to-hemoglobin ratio at admission in predicting 30-day mortality in patients with acute upper gastrointestinal bleeding (UGIB). Methods: Patients who presented to the emergency department due to acute UGIB between January and December 2024 were included in the study. The laboratory parameters at the time of admission, medication usage, endoscopic diagnoses, and 30-day mortality rates of the patients were investigated. It was investigated whether there were differences in biochemical parameters such as hemoglobin, hematocrit, neutrophil, lymphocyte, platelet, international normalized ratio (INR), pH, lactate, blood urea nitrogen (BUN), creatinine, C-reactive protein (CRP), albumin, BUN to creatinine ratio, and lactate to hemoglobin ratio between patients with and without 30-day mortality. In addition, the relationship between mortality, drug use, and endoscopic diagnoses was examined. Results: A total of 241 patients participated in the study. Of the participants in the study, 79 (32.8%) were women and 162 (67.2%) were men. The average age of the patients was 70 years. The most common causes of bleeding were, in order, bulbar ulcer (n = 84, 34.9%) and gastric ulcer (n = 79, 32.8%). A total of 15 (6.2%) patients developed mortality within 30 days. In the mortality group, lymphocyte (p = 0.016) and albumin (p = 0.026) values were statistically low, while INR (p = 0.041), creatinine (p = 0.020), CRP (p < 0.01), lactate (p = 0.014) and lactate to Hb ratio (LHR) (p = 0.012) values were significantly high. In cases of bleeding due to malignancy, mortality was higher. No association was found between medication use and mortality. Conclusions: In this exploratory study, the LHR showed potential as an adjunctive biomarker for estimating 30-day mortality in patients with non-variceal acute UGIB. It can be readily calculated based on common laboratory values, does not necessitate complex scoring systems, and can help with quick risk assessment in emergency conditions. Large, multicenter prospective studies are required to confirm prediction accuracy as well as identify optimum cutoff values for clinical application.