Introspection is a fundamental part of our mental lives. Nevertheless, its reliability and its underlying cognitive architecture have been widely disputed. Here, I propose a principled way to model introspection. By using time-tested principles from signal detection theory (SDT) and extrapolating them from perception to introspection, I offer a new framework for an introspective signal detection theory (iSDT). In SDT, the reliability of perceptual judgments is a function of the strength of an internal perceptual response (signal- to-noise ratio) which is, to a large extent, driven by the intensity of the stimulus. In parallel to perception, iSDT models the reliability of introspective judgments as a function of the strength of an internal introspective response (signal-to-noise ratio) which is, to a large extent, driven by the intensity of conscious experiences. Thus, by modelling introspection after perception, iSDT can calibrate introspection’s reliability across a whole range of contexts. iSDT offers a novel, illuminating way of thinking about introspection and the cognitive processes that support it.