1) A large obstacle in food web ecology is the time and effort required to adequately describe the structure of a food web using individual predator guts. Food web models such as the allometric diet breadth model (ADBM) can be used to circumvent this problem by predicting the interactions based on easily measured characteristics, such as the size of organisms. However, diet data such as that which comes from analysis of predator guts is still required to parameterise these food web models, and collecting and analysing these data from the field is an expensive and time-consuming task. Therefore, it is important to know how many predator guts are required to parameterise food web models to obtain food web structures with high accuracy and precision. 2) Here, we explore seven exceptionally well-characterised food webs and determine the minimum number of predator guts needed to accurately predict their structure using the ADBM. We use Bayesian computation to parameterise the ADBM, and true skill statistics to measure the goodness of fit, and do so while varying the number of predator guts used in the parameterisation to test the effect of sampling effort. 3) We found that relatively few, and many fewer than were actually collected, predator guts can be used to parameterise the ADBM. The lowest number of predator guts was 27% of the number of available predator guts. The number of predator guts required to accurately characterise food webs increases by ∼ 7 ±2.2 guts for 10 units increase in the number of trophic links and ∼ 9 ±4.7 guts for a unit increase in the number of species. 4) These results suggest that one need not collect and analyse such a large quantity of predator guts in order to adequately predict the structure of a food web, thereby reducing sampling effort considerably, while having little effect on precision or accuracy of predictions.