Spoilage in meat is the result of the action of microorganisms and results in changes of meat and microbial metabolism. This process may include pathogenic food poisoning bacteria such as Salmonella typhimurium, and it is important that these are differentiated from the natural spoilage process caused by non-pathogenic microorganisms. In this study we investigated the application of metabolic profiling using gas chromatography-mass spectrometry, to assess the microbial contamination of pork. Metabolite profiles were generated from microorganisms, originating from the natural spoilage process and from the artificial contamination with S. typhimurium. In an initial experiment, we investigated changes in the metabolic profiles over a 72 hour time course at 25 °C and established time points indicative of the spoilage process. A further experiment was performed to provide in-depth analysis of the metabolites characteristic of contamination by S. typhimurium. We applied a three-way PARAllel FACtor analysis 2 (PARAFAC2) multivariate algorithm to model the metabolic profiles. In addition, two univariate statistical tests, two-sample Wilcoxon signed rank test and Friedman test, were employed to identify metabolites which showed significant difference between natural spoiled and S. typhimurium contaminated samples. Consistent results from the two independent experiments were obtained showing the discrimination of the metabolic profiles of the natural spoiled pork chops and those contaminated with S. typhimurium. The analysis identified 17 metabolites of significant interest (including various types of amino acid and fatty acid) in the discrimination of pork contaminated with the pathogenic microorganism.