To represent something as absent, one must know that they would know if it were present. This form of counterfactual reasoning critically relies on a mental self-model: a simplified schema of one's own cognition, which specifies expected perceptual and cognitive states under different world states and affords better monitoring and control over cognitive resources. Here I propose to use inference about absence as a unique window into the structure and function of the mental self-model. I draw on findings from low-level perception, visual search, and long-term memory, in support of the idea that self-knowledge is a computational bottleneck for efficient inference about absence, and show that alternative "direct perception" and "heuristic" accounts either fail to account for empirical data, or implicitly assume a self-model. I end with a vision for an empirical science of self-modelling, where inference about absence provides a cross-cutting framework for probing key features of the mental self-model that are not accessible for introspection.