Tall buildings are engineering marvels designed to withstand environmental forces such as wind and seismic activities. Among the key factors influencing their structural integrity is damping, a phenomenon that governs how a building dissipates energy from vibrations. Unlike mass and stiffness, damping is difficult to estimate due to the complex interplay of materials, frictional effects, and structural interactions. This article explores how a data-driven, probabilistic approach improves the understanding and prediction of damping behavior in high-rise structures.