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Summary: Predicting the number of interactions among species in a food web is an important task. These trophic interactions underlie many ecological and evolutionary processes, ranging from biomass fluxes, ecosystem stability, resilience to extinction, and resistance against novel species. We investigate and compare several ways to predict the number of interactions in food webs. We conclude that a simple beta-binomial model outperforms other models, with the added desirable property of respecting biological constraints. We show how this simple relationship gives rise to a predicted distribution of several quantities related to link number in food webs, including the scaling of network structure with space and the probability that a network will be stable. The Bigger Picture: Understanding the functions, stability, resilience, and dynamics of ecological communities requires the investigation of the structure of their networks of interactions. Perhaps the most challenging issue in the study of such networks is that the sampling of ecological interactions is a strenuous task, and as a result, the availability of empirical data is limited. In this contribution we derive a realistic and performant statistical model to predict the number of interactions in a food web from its number of species. Our model could be used as a first-order approximation of network structure. As such, it makes the large-scale study and comparison of ecological networks more accurate and accessible. For instance, the vulnerability of food webs to perturbations could be explored using our model at the regional, continental, or global scales.