GC-MS based metabolome studies aim for the complete identification and relative or absolute quantification of metabolites in complex extracts from a large diversity of biological materials. The resulting high-throughput chromatography data files are typically processed following two complementary workflows, namely, fingerprinting and profiling. For fingerprinting studies all observed mass features, here called mass spectral tags (MSTs), are quantified in a nontargeted and (within the limits of the GC-MS technology) comprehensive approach. Fingerprinting allows for the discovery of MSTs, which, in the sense of a biomarker, indicate significant changes of metabolite pool sizes. The significance and relevance of such MSTs are typically tested in comparison to standardized reference samples. Only after this confirmation step are the relevant MSTs identified and the underlying metabolic biomarkers elucidated. Both the metabolite fingerprinting and profiling approaches are essential to modern biotechnological investigations. Studies which are aimed at establishing the substantial equivalence at metabolic level or aim to breed for optimum quality of human food or animal feed especially benefit from the potential to discover novel unforeseen metabolic factors in fingerprinting approaches and from the option to demonstrate unchanged pool sizes of known metabolites in the metabolic profiling mode. As GC-MS technology represents one essential element which contributes to investigations of substantial equivalence, we have developed a dedicated software tool, the TagFinder chromatography data preprocessing suite, which has all essential functions to support both fundamental workflows of modern metabolomic studies. In this chapter, we describe the TagFinder software and its application to the assessment of metabolic phenotypes in fingerprinting and profiling analyses.