Bioinformatic tools are required to carry out essential functions such as statistical analyses and database func-tionalities. Now, they are also needed for one of the most difficult tasks, helping researchers decide which metabo-lites are the most biologically meaningful. This can be achieved through aiding the identification process, reducing feature redundancy, putting forward better candidates for tandem mass spectrometry (MS/MS), speeding up or automating the workflow, deconvolving the feature list through meta-analysis or multigroup analysis, or using stable isotopes and pathway mapping. This review thus focuses on the most recent and innovative bioinformatic advancements for identifying metabolites.