Metabolic fingerprinting is a relatively young scientific discipline requiring robust, yet flexible and fit-for-purpose analytical methods. Here, we introduce a simple approach to select reversed phase LC systems with electrospray MS detection for fingerprinting of polar and amphiphilic plant metabolites. The approach does not rely on isotopic labeling or biological origin of sample constituent and can also be used for non-biological matrices (e.g., oil or sewage sludge) or for other optimization purposes (e.g., mass spectrometric source parameterization). The LC systems varied in column chemistry and temperature, mobile phase pH/additive, gradient steepness/eluotropic strength, and electrospray mode of operation. The systems were evaluated based on the number of features detected using the matchedFilter algorithm from XCMS and the repeatability of this detection across analytical replicates. For negative ion mode detection, the best performances were obtained with an HSS T3 column operated at low pH, which produced a 3-fold increase in the number of reliable features extracted compared with the worst system. The best system for positive ion mode (i.e., the BEH C18 column operated at intermediate pH) only produced a 50 % increase in the number of reliable features. The data also indicate that baseline removal is unavoidable for reliable intensity estimations using peak areas, and that peak heights may be a more robust measure of intensity when baselines cannot be completely removed or in case of coelution, fronting or tailing.