The ability to monitor interactions between individuals over time can provide us with information on life histories, mating systems, behavioural interactions between individuals and ecological interactions with the environment. Tracking individuals over time has traditionally been a time- and often a cost-intensive exercise, and certain types of animals are particularly hard to monitor. Here we use canonical discriminant analysis (CDA) to identify individual Mexican Ant-thrushes using data extracted with a semi-automated procedure from song recordings. We test the ability of CDA to identify individuals over time, using recordings obtained over a 4-year period. CDA correctly identified songs of 12 individual birds 93.3% of the time from recordings in one year (2009), while including songs of 18 individuals as training data. Predicting singers in one year using recordings from other years indicated some instances of variation, with correct classification in the range of 67–88%; one individual was responsible for the great majority (66%) of classification errors. We produce temporal maps of the study plot showing that considerably more information was provided by identifying individuals from their songs than by ringing and re-sighting colour-ringed individuals. The spatial data show site fidelity in males, but medium-term pair bonds and an apparently large number of female floaters. Recordings can be used to monitor intra- and intersexual interactions of animals, their movements over time, their interactions with the environment and their population dynamics.