Objectives: Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) and Fourier Transform Infrared-Spectroscopy (FTIR-S) as diagnostic alternatives to DNA-based methods for the detection of Pseudomonas aeruginosa sequence type (ST) 175 isolates involved in a hospital outbreak. Methods: Twenty-seven P. aeruginosa isolates from a 2014 outbreak in the Hematology department of our hospital were previously characterized by PFGE and WGS. Besides, 8 P. aeruginosa isolates were analyzed as unrelated controls. MALDI-TOF MS spectra were acquired by applying the colony on the MALDI target plate followed by 1 µl of formic acid 100% and 1 µl of HCCA matrix. For the analysis with FTIR-S, colonies were resuspended in 70% ethanol and sterile water according to the manufacturer instructions. Spectra from both methodologies were analyzed using Clover Biosoft® software, that allowed data modelling using different algorithms and validation of the classifying models. Results: Three outbreak-specific biomarkers were found at 5169, 6915 and 7236 m/z in MALDI-TOF MS spectra. Classification models based on these three biomarkers showed the same discrimination power displayed by PFGE. Besides, K-Nearest Neighbor algorithm allowed the discrimination of the same clusters provided by whole-genome sequencing and the validation of this model achieved 97.0% correct classification. On the other hand, FTIR-S showed a discrimination power similar to PFGE and reached correct discrimination of the different STs analyzed. Conclusions: The combination of both technologies evaluated, paired with Machine Learning tools, may represent a powerful tool for real-time monitoring of high-risk clones and isolates involved in nosocomial outbreaks.