Occupants exercise adaptive actions in response to discomforting environmental stimuli in an attempt to restore their comfort. These responses to adaptive actions are either ignored (conventional PMV models) or handled in an aggregated way (adaptive thermal comfort models). Furthermore the availability of adaptive actions and their effectiveness tends to be particular to a given building and climatic context. A good model should predict the probability with which available adaptive actions will be exercised and the feedback to occupants’ perceived comfort from these specific actions. In this paper we introduce a new modelling framework which does just that. Informed by results from detailed monitoring campaigns we first present a model to predict the probability distribution of thermal sensation in non air-conditioned buildings and a new method for deducing comfort zones in such buildings. We then introduce a methodology for combining recent advances in the prediction of occupants’ adaptive actions with the comfort feedback from these actions. We demonstrate how thermal sensation probability distribution may be deduced accounting for exercised adaptive actions and develop a comprehensive model for predicting comfort temperature which explicitly accounts for probable adaptive actions and their thermal feedback. We go on to describe how this modelling framework, which may be readily applied for thermal comfort prediction in specific building and climatic contexts, significantly deepens our understanding of adaptive thermal comfort mechanisms. Finally, we also describe ways of handling individuals’ diversity within this new framework as well as how it may be applied to evaluate visual and olfactory comfort.