Repetitive samples of three strains of the mould Penicillium were subjected to pyrolysis-gas chromatography (Py-GC). From the chromatograms, 26 peak heights were used in a subsequent SIMCA pattern recognition analysis. This data analysis gives a marked improvement in the classification of the samples (100% correct, 85% unique) in comparison with the traditional analysis based on the average chromatogram of each class (92% correct, 45% unique). The data analytical method is described in detail using the Py-GC data as an illustration.