Accurate pre-endoscopic risk stratification is essential in acute upper gastrointestinal bleeding (UGIB). Established scores predict mortality but have limited ability to identify patients requiring early therapeutic endoscopy. We developed and temporally validated a pre-endoscopic machine learning model to predict 30-day mortality and early (≤24 h) endoscopic hemostatic intervention and assessed model interpretability.