Mammals are able to distinguish conspecifics based on vocal cues, and the acoustic structure of mammal vocalizations is directly affected by the anatomy and action of the vocal apparatus. However, most studies investigating individual patterns in acoustic signals do not consider a vocal production-based perspective. In this study, we used the source- filter model of vocal production as a basis for investigating the acoustic variability of fallow deer groans. Using this approach, we quantified the potential of each acoustic component to carry information about individual identity. We also investigated if cues to individual identity carry over among the two groan types we describe: common and harsh groans. Using discriminant function analysis, we found that variables related to the fundamental frequency contour and the minimum frequencies of the highest formants contributed most to the identification of a given common groan. Common groans were individually distinctive with 36.6% (53.6% with stepwise procedure) of groans assigned to the correct individual. This level of discrimination is approximately six times higher than that predicted by chance. In addition, univariate anovas showed significant inter-individual variation in the minimum formant frequencies when common and harsh groans were combined, suggesting that some information about individuality is shared between groan types. Our results suggest that the sound source and the vocal tract resonances act together to determine groan individuality and that enough variation exists to potentially allow individual recognition based on groans.