This study describes a computer-based technique for classifying and identifying bacterial samples using Fourier-transform infrared spectroscopy (FT-IR) patterns. Classification schemes were tested for selected series of bacterial strains and species from a variety of different genera. Dissimilarities between bacterial IR spectra were calculated using modified correlation coefficients. Dissimilarity matrices were used for cluster analysis, which yielded dendrograms broadly equated with conventional taxonomic classification schemes. Analyses were performed with selected strains of the taxa Staphylococcus, Streptococcus, Clostridium, Legionella and Escherichia coli in particular, and with a database containing 139 bacterial reference spectra. The latter covered a wide range of Gram-negative and Gram-positive bacteria. Unknown specimens could be identified when included in an established cluster analysis. Thirty-six clinical isolates of Staphylococcus aureus and 24 of Streptococcus faecalis were tested and all were assigned to the correct species cluster. It is concluded that: (1) FT-IR patterns can be used to type bacteria; (2) FT-IR provides data which can be treated such that classifications are similar and/or complementary to conventional classification schemes; and (3) FT-IR can be used as an easy and safe method for the rapid identification of clinical isolates.