Stomatal regulation presumably evolved to optimize CO2 for H2O exchange in response to changing conditions. If the optimization criterion can be readily measured or calculated, then stomatal responses can be efficiently modelled without recourse to empirical models or underlying mechanism. Previous efforts have been challenged by the lack of a transparent index for the cost of losing water. Yet it is accepted that stomata control water loss to avoid excessive loss of hydraulic conductance from cavitation and soil drying. Proximity to hydraulic failure and desiccation can represent the cost of water loss. If at any given instant, the stomatal aperture adjusts to maximize the instantaneous difference between photosynthetic gain and hydraulic cost, then a model can predict the trajectory of stomatal responses to changes in environment across time. Results of this optimization model are consistent with the widely used Ball–Berry–Leuning empirical model (r2 > 0.99) across a wide range of vapour pressure deficits and ambient CO2 concentrations for wet soil. The advantage of the optimization approach is the absence of empirical coefficients, applicability to dry as well as wet soil and prediction of plant hydraulic status along with gas exchange. Current land surface models struggle to represent the complex and species‐specific manner by which stomata respond to environmental cues, especially soil drought. This paper offers a solution to this problem by assuming that the goal of stomatal regulation is to maximize photosynthetic gain minus hydraulic cost. A trait‐ and process‐based ‘profit‐maximizing’ algorithm predicts realistic stomatal behaviour in response to the gamut of environmental stimuli. This new approach to stomatal optimization theory may prove useful in large‐scale modelling of responses to climate change.