The Predicted Mean Vote (PMV) serves to forecast the thermal sensation of a group by examining human thermal load, a methodology widely recognized and embraced by thermal comfort standards in the design of energy-efficient buildings that aim for optimal thermal comfort. Despite its utility, the excessively simplistic portrayal of skin evaporative heat loss in thermal load computations has frequently led to reported discrepancies between PMV predictions and real-world thermal sensation votes. This chapter endeavors to enhance the PMV model by integrating the concept of skin wettedness from the standard effective temperature model. The standard effective temperature model, which incorporates advanced human thermoregulatory mechanisms, can reasonably predict skin wettedness based on key physiological parameters such as core temperature, skin temperature, and peripheral blood flow. This skin wettedness parameter is subsequently utilized to calculate skin evaporative heat loss, substituting the oversimplified method conventionally employed in PMV calculations. The modified PMV with an improved representation of skin evaporative heat loss is validated against the ASHRAE Global Thermal Comfort Database II, the largest of its kind, encompassing diverse climate types, building categories, and HVAC systems. In comparison to the original PMV, the modified version demonstrates significant enhancements in the overall accuracy and robustness of thermal sensation prediction, with improvements of 64% and 32%, respectively. This chapter makes a valuable contribution to the ongoing refinement of PMV and paves the way for updates to thermal comfort standards.