Passive acoustic monitoring has proven effective for broad-scale population surveys of acoustically active species, making it a valuable tool for conserving endangered species like many Anurans (and some carnivores). However, successful automated classification of anuran vocalizations in large audio datasets has been limited. We deployed five autonomous recording units at three known breeding areas of the declining Yosemite toad to supplement ongoing, human survey efforts. We analyzed the audio data with the BirdNET algorithm, which was originally developed for birds but has been expanded to include the Yosemite toad and the sympatric Pacific chorus frog, among other non-avian classes. We achieved high classification accuracy for both species, and efficiently detected the two species in thousands of hours of audio data. For both species, (1) vocalization counts were correlated among three co-deployed recording units but varied substantially in magnitude, (2) we obtained phenological data about nearly the entire breeding period, and (3) we observed diel cycles in vocal activity. Vocalization counts are a precursor to acoustic-based abundance indices, while phenological data could reveal shifts in breeding linked to climate change, two types of information that could improve the conservation of vocally active amphibians. Finally, we extend the results presented here to illustrate how these techniques are relevant to population monitoring of carnivores.