Coyotes Canis latrans, bobcats Lynx rufus and gray foxes Urocyon cinereoargenteus are all common mammalian mesopredators in coastal California and are found sympatrically in much of North America. Scats produced by these three animals are quite similar, but have historically been differentiated largely by morphology. I tested the efficacy of morphological classification of scat to species by building predictive models for species identification with a set of well-described, DNA-verified scats. I compiled a database of morphological, biogeochemical and contextual traits for a set of 122 DNA-verified bobcat, coyote and gray fox scats. I then took two different approaches to predictive modeling, using both discriminant function analysis and random forests to predict scats to species. I found significant differences among species in only three (diameter, mass and C:N ratio) of the 12 variables I considered. Linear discriminant analysis was only 71% predictive with the inclusion of a non-morphological variable in addition to morphological traits. Random forests similarly had only a 62% correct classification rate. Although scat morphology is not generally diagnostic to species for this set of mammalian mesopredators, these predictive morphometric models may still prove to be useful first-pass identification tools. The linear discriminant model in particular is able to identify scats with certain traits to species with a high degree of confidence, lending credence to the idea of ‘end member morphologies’ for scats produced by these different animals. I suggest that researchers take similar measurements to either use in the morphometric models presented here, or build similar models for their target species. These results also suggest that some previous studies using morphology-based scat identifications may have misrepresented or misinterpreted diets and space use by these sympatric mammals.