Untargeted metabolomics is an analytical chemistry approach dedicated for the analysis of small biomolecules called “metabolites”. One of its strengths is the ability of covering wide ranges of metabolic information in biological systems. However, exhaustive coverage of information is challenging from a chemical-analytical point of view. In fact, the widely different physical-chemical properties of molecules (e.g. polarity, acidity/basicity) make the study of various types of metabolites complicated. It demands critical methodological optimizations. Nevertheless, for untargeted approaches, “optimal conditions” are also hard to be defined and judged. The current work is focusing on the crucial step of meta-metabolome extraction. It seeks to develop an “exhaustive” extraction protocol able to extract different types of metabolites by covering a wide range of polarity. This is in the framework of developing the “Environmental Metabolic Footprinting” untargeted metabolomics-based approach [1,2], aiming to assess the environmental fate and impact of complex (bio)pesticides application on soil. Indeed, optimizing a method able to analyze diverse kind of metabolites can assure a wide range of information needed to assess the fate of the pesticide (xenometabolites) and its impact on soil’s biodiversity (endometabolites). In this objective, 5 extraction protocols based on solvents and mixtures with different polarities were developed and applied on 2 different types of soils, with 3 different environmental conditions (control, spiked with a synthetic pesticide, spiked with a natural pesticide). So far, 150 samples were extracted and analyzed with a broadband LC-HRMS method that was set-up for the purpose. The collected data were then handled and analyzed with various types of multivariate statistical analyses that were optimized in order to assess the “optimal” protocol, based on 4 main criteria, respectively: 1) the ability to widen the band of the extracted metabolites (qualitative), 2) the higher extraction yield (quantitative), 3) the repeatability of the extraction, and 4) the reliability in discrimination between spiked and control groups (EMF objective). The study showed that widening the polarity range for the extraction protocol, using miscible solvents with different properties was applicable and resulted for a significant ability in extracting a wide range of metabolites originating from both pesticide residues and soil endometabolome. It also showed comparable quantitative results and better repeatability comparing to other classical protocols. In addition, the study suggests multivariate analyses as suitable tool not only for data processing for biological studies, but also for developing analytical methods and protocols, as it can give holistic explanations about the large datasets acquired. Hence, in other words, untargeted metabolomics were used in order to improve the analytical method dedicated for an untargeted meta-metabolomics approach. [1]: Patil et al. 2016. Sci. Total Environ. 566–567:552–558. [2]: Salvia et al. 2018. Environ. Sci. Pollut. Res. 25(30):29841–29847.