The analysis of the chemical composition of fingerprints is important for the development and improvement of existing fingerprint enhancement techniques. This study demonstrates the first analysis of a latent fingerprint sample, using an optimized CE-MS method. In total 12 amino acids were detected in the fingerprint sample. MS/MS fragmentation was used to provide additional identity confirmation, for which eight of the twelve detected amino acids generated confirmatory product ions. Nine amino acids were quantified and their relative abundances were consistent with previous studies with serine and glycine being the most abundant. The successful detection of amino acids from latent fingerprints demonstrates that CE-MS is a potential future technique for further study of such compounds in fingerprint samples.