AimArtisanal fisheries account for 40% of the world's fisheries catch, yet its environmental impacts remain poorly understood. This is especially the case in developing countries. In this study, we sought to integrate Local Fisher's Knowledge with distribution modelling to estimate the annual bycatch of Titicaca Grebe (Rollandia microptera), an endangered endemic bird from Lake Titicaca whose main anthropogenic threat is bycatch.LocationLake Titicaca, Peru and Bolivia.MethodsWe conducted transect and point counts of fishing nets in March–September 2022 and conducted interviews with fishers across the Lake Titicaca region. Using bathymetry, distance from shore, distance from a settlement, distance from the protected area, presence/absence of aquaculture, distance from aquaculture, and wetland cover, we constructed a distribution model of fisheries using maximum entropy modelling. We conducted interviews with fishers asking about the frequency of grebe bycatch and conducted short‐term monitoring at various sites while conducting transect points for dead grebes.ResultsWe estimate 3270 km2 of the surface area of Lake Titicaca is used for fishing, which amounts to 39.40% of the lake's surface area. The area under the curve (AUC) of the distribution model was 0.89 and the True Skill Statistic was 0.67, which suggests maximum entropy modelling can model fisheries occurrence. The results of our interviews suggested a biologically implausible large number of grebes caught as bycatch annually. The cultural context of the interviews, including potential influences of non‐response and social‐desirability bias, being with fishers who often view the Titicaca Grebe as a nuisance species, might have caused over‐reporting of bycatch and hence led to these implausible figures.Main ConclusionsIt is possible to map fisheries using distribution models as one might with species. However, obtaining accurate measures of fisheries bycatch through interviews is more difficult, due to cultural factors which affect the accuracy in fisher's responses. While we hope that this method provides a low‐cost alternative to monitoring, it is not a suitable replacement for it.