Physiologists typically assume that optimal thermal comfort can only be achieved by minimizing thermoregulatory efforts. People are thus believed to be thermally comfortable with a mean skin temperature of 33–34 °C and minimized sweating rate at a low metabolic rate. Many heat balance comfort models are established based on these fixed comfort criteria. However, occupants’ thermal requirements are found to be more flexible and dynamic because of physiological and psychological adaptions. In this study, dynamic comfort criteria (DCC) are proposed to consider the adaption in the PMV model. Occupants tend to accept a lower skin temperature in a cold climate and a slightly higher sweating rate in a hot climate. We provide two methods to infer DCC based on ASHRAE thermal comfort database II. One is to develop a generalized DCC that can be applied globally. Another is to use Bayesian calibration to develop a customized DCC that further localizes the thermal requirements. With DCC, the deficiency of the PMV and the adaptive model can be largely eliminated. Unlike PMV, the model with DCC performs consistently in different operation modes. DCC is conceptually different from actual physiological responses, although they can sometimes be close to each other in values. The study paves the road for unifying comfort theories and equipping traditional comfort models with the ability to re-learn.