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Accounting for variation in prey mortality and predator metabolic potential arising from spatial variation in consumption is an important task in ecology and resource management. However, there is no statistical method for processing stomach content data that accounts for fine‐scale spatio‐temporal structure while expanding individual stomach samples to population‐level estimates of predation. Therefore, we developed an approach that fits a spatio‐temporal model to both prey‐biomass‐per‐predator‐biomass data (i.e. the ratio of prey biomass in stomachs to predator weight) and predator biomass survey data, to predict "predator‐expanded‐stomach‐contents" (PESCs). PESC estimates can be used to visualize either the annual landscape of PESCs (spatio‐temporal variation), or can be aggregated across space to calculate annual variation in diet proportions (variation among prey items and among years). We demonstrated our approach in two contrasting scenarios: a data‐rich situation involving eastern Bering Sea (EBS) large‐size walleye pollock (Gadus chalcogrammus, Gadidae) for 1992–2015; and a data‐limited situation involving West Florida Shelf red grouper (Epinephelus morio, Epinephelidae) for 2011–2015. Large walleye pollock PESC was predicted to be higher in very warm years on the Middle Shelf of the EBS, where food is abundant. Red grouper PESC was variable in north‐western Florida waters, presumably due to spatio‐temporal variation in harmful algal bloom severity. Our approach can be employed to parameterize or validate diverse ecosystem models, and can serve to address many fundamental ecological questions, such as providing an improved understanding of how climate‐driven changes in spatial overlap between predator and prey distributions might influence predation pressure. [ABSTRACT FROM AUTHOR]