Behavioral economics has long modeled loss aversion as a fixed parameter within Prospect Theory. The Loss Aversion Distribution (LAD, 2024), introduced by Dr. Daniel Koh, is the first in the world to conceptualize loss aversion as a probability distribution rather than a constant value. Though still theoretical, LAD marks a major step toward a distributional understanding of human decision-making, capturing behavioral diversity across individuals and contexts. This session explores how LAD reshapes behavioral modeling, bridges psychology with data science, and opens new frontiers for quantifying human bias through statistical inference — redefining the foundations of behavioral economics for the next generation of researchers and practitioners.