The identification of filamentous fungi by matrix-assisted laser desorption/ionization–time of flight mass spectrometry (MALDI–TOF MS) represents a challenge due to their complex taxonomy and the lack of comprehensive databases. The aim of this study was to evaluate the current status of available MALDI–TOF MS databases for the identification of dermatophytes, including commercial, in-house, and web-based databases. We collected 289 dermatophyte strains from different centers and analyzed them using four databases and a combination of them. The combination of commercial and in-house databases was shown to improve the identification rate and accuracy at the species level. For Trichophyton rubrum, the concordance among all databases was above 90.0%. For the T. mentagrophytes group, correct identification at the species level ranged from 30.0 to 78.9%, depending on the database, and showed very low agreement among them. The addition of the novel species T. japonicum to our in-house database resulted in the successful identification of this species. On the other hand, T. interdigitale and T. tonsurans were the species most frequently misidentified by MALDI–TOF MS. Through deep spectra analysis of both species, up to 29 protein peaks were found to be suitable for their differentiation, demonstrating the potential of peak analysis in differentiating closely related species. In conclusion, improvements of the databases with new strains resulted in increased identification accuracy at the species level. This, combined with peak analysis, could improve the overall identification of dermatophytes by MALDI–TOF MS in clinical laboratories.