Recent advances in molecular techniques have provided new tools for confirming species identities, however they can be expensive and results are not immediately available. Myotis lucificugus and M. yumanensis are morphologically cryptic species of bats sympatric in western North America that can be difficult to distinguish in the field. We evaluated a set of models that used morphological and echolocation call characters obtained in the field to predict species identity as determined by DNA analysis. We constructed models using data from 98 M. lucifugus and 100 M. yumanensis captured throughout the Pacific Northwest from which we had obtained high-quality, time-expansion recordings of their echolocation calls. The best model for distinguishing the species combined forearm length and characteristic frequency of echolocation calls and was able to identify 92% of M. lucifugus and 91% of M. yumanensis individuals, with ≥95% confidence. We evaluated the applicability of our model by testing it on additional datasets. Our model correctly classified 83% of M. lucifugus (n = 30) and 93% of M. yumanensis (n = 29) individuals captured in north-central Oregon, whose echolocation calls were recorded using a zero-crossings echolocation detection system. It also correctly classified 86% of M. lucifugus (n = 22) and 85% of M. yumanensis (n = 26) individuals, captured throughout our study area, for which only poor-quality time-expansion recordings of echolocation calls were obtained. Combining morphometrics with echolocation call characteristics may be a useful approach for distinguishing among pairs of cryptic species of bats in other areas.