The rise of “omics sciences”, with high-throughput measurements of cellular macromolecules DNA, RNA and proteins, has opened up avenues to the measurement of cellular small organic molecules, which is the foundation of metabolomics. The metabolome is defined as the complete set of small organic molecules produced by a given cell in a given time and space. Metabolomics is therefore defined as the set of analytical techniques used to measure a large subset of the metabolome. In this chapter we focus on the mass spectrometry (MS) platforms applied to metabolomics, under the assumption that no single analytical platform is capable of measuring all of the metabolome. The main MS-based metabolomics approaches are contextualized to molecular classes and metabolic partition targeted in experiment, and a guide for experimental design is explored. Experimental design includes the most recent analytical and computational resources that point towards the possible factors that influence the analysis and, consequently, the results. We seek to enable metabolomics practitioners to correctly design experiments, based on specific biological questions, and to keep in mind which workflow is best suited to the study goal for the metabolites being sampled. In addition, we discuss several issues surrounding the analytical platform and the main MS parameters for acquiring metabolomics data, as well as the application of quality control, and finally the statistical analysis from data. The main goal of metabolomics is the understanding of phenotypical changes through unbiased data analysis interpretation. To achieve this goal, an integrated approach from experimental design to data processing is required.