The ‘prebound effect’ characterises how average heating energy consumption in older homes is consistently lower than these buildings' calculated energy ratings, and helps explain why energy savings from thermal upgrades are often lower than anticipated. This paper explores the conceptual links between prebound and rebound effects and aims to quantify these behavioural effects. It applies the resulting mathematical model to empirical examples of actual and calculated energy consumption at scales of individual dwelling and national housing stock. These show that the rebound effect, as defined in econometrics literature, can only indicate proportionate reductions in energy consumption and can mask high levels of absolute consumption. The prebound effect, however, can identify under- and over-consumption regardless of rebound effects. A combination of high prebound effect and low income suggests fuel poverty, and the rebound effect here is less relevant regarding total energy consumption. Policymakers should identify housing with high prebound effects in order to eliminate fuel poverty, and be aware of inaccuracies in calculating payback time where economic viability of retrofits is mandated. Further research is needed to understand motivations and practices in households that have high prebound effects and to identify specific priority groups for thermal retrofit policy.