Powered by AI (Copilot) Abstract Predicting the relative sweetness of compounds remains challenging due to the subjectivity and variability inherent in human sensory panels. This study presents a machine-learning-based algorithm that forecasts relative sweetness values (RSV, sucrose = 1.00) using only readily calculable two-dimensional physicochemical descriptors, including molecular size and geometry, hydration-related indices, and related parameters. The model employs an en