Polyethylene glycol (PEG) is one of the most common polymer contaminations in MS samples. At present, the detection of PEG and other polymers relies largely on manual inspection of raw data which is laborious and frequently difficult due to sample complexity and retention characteristics of polymer species in reversed phase chromatography. We developed a new strategy for the automated identification of PEG molecules from MSMS data using protein identification algorithms in combination with a database containing “PEG-proteins”. Through definition of variable modifications, we extend the approach for the identification of commonly used PEG-based detergents. We exemplify the identification of different types of polymers by static nanoESI-MSMS analysis of pure detergent solutions and data analysis using Mascot. Analysis of LC-MSMS runs of a PEG contaminated sample by Mascot identified 806 PEG-spectra originating from four PEG species using a defined set of modifications covering PEG and common PEG-based detergents. Further characterization of the sample for unidentified PEG species using error tolerant and mass tolerant searches resulted in identification of 3409 and 3187 PEG related MSMS spectra, respectively. We further demonstrate the applicability of the strategy for Protein Pilot and MaxQuant.