Hydrogen is increasingly being explored as an energy carrier to support a decarbonized energy economy. Both the direct utilization of hydrogen and its blending with conventional fuels such as natural gas are under active consideration to meet the stringent emissions regulations faced by the energy sector. Among the combustion parameters affected by hy­drogen, the turbulent burning velocity (ST) plays a central role in determining combustor operability limits, influencing blowoff, flashback, and combustion instabilities. The impact of hydrogen on ST becomes particularly complex under lean conditions and at high pres­sures, where traditional scaling models for ST, based largely on root-mean-square turbulent velocity fluctuations and the unstretched laminar flame speed, are inadequate. This dissertation focuses on the co-development of data-driven and physics-based mod­eling frameworks to predict ST in hydrogen-fueled premixed flames based on leading-point concepts.