Headspace GC is frequently used for aroma profiling thanks to its ability to naturally exploit the volatility of aroma compounds, and also to provide chemical information on sample composition. Its main advantages rely on simplicity, no use of solvent, amenability to automation, and the cleanliness of the extract. In the present contribution, the most effective sampling (dynamic extraction), separation (multidimensional gas chromatography) and detection (mass spectrometry) techniques for untargeted analysis are exploited in combination, showing their potential in unraveling aroma profiles in fruit beers. To complete the overall analytical process, a neat workflow for data analysis is discussed and used for the successful characterization and identification of 5 different beer flavors (berries, cherry, banana, apple, and peach). From the technical viewpoint, the coupling of purge-and-trap, comprehensive two-dimensional gas chromatography, and mass spectrometry makes the global methodology unique, and it is for the first time discussed. A (low-)flow modulation approach allowed for the full transfer into the second dimension with MS-compatible flow (< 7 mL/min), avoiding the need of splitting before detection and making the overall method sensitive (1.2-5.2 fold higher S/N compared to unmodulated GC conditions) and selective. This article is protected by copyright. All rights reserved.