In fields such as food safety and environmental chemistry, ensuring safety is greatly challenged by large numbers of unknown substances occurring. Even with current state of the art mass spectrometers, dealing with non-identified substances is a very laborious process as it includes structure elucidation of a vast number of unknowns, of which only a fraction may be relevant. Here, we present an exploration and prioritization approach based on high resolution mass spectrometry. The method uses algorithm-based precursor/product-ion correlations on Quadrupole-Time of Flight (Q-TOF) MS/MS data to retrieve the most likely chemical match from a structure database. In addition, TOF-only data is used to estimate analyte concentration via semi-quantification. The method is demonstrated in recycled paper food contact material (FCM). Here, 585 chromatographic peaks were discovered, of which 117 were unique to the sample and could be tentatively elucidated via accurate mass, isotopic pattern, and precursor/product-ion correlations. Nearly 85% of these 117 peaks were matched with database entries, which provided varying certainty of information about the analyte structure. Semi-quantitative concentration ranges of investigated compounds were between 0.7 μg dm-2 and 1600 μg dm-2. With this data, a subgroup of chemicals was risk-categorized and prioritized using the most likely candidate structure(s) obtained. Prioritization based on expected health impact was possible using the tentatively assigned data. Overall, the described method is a valuable chemical exploration tool for non-identified substances, but also may be used as a preliminary prioritization tool for substances expected to have the highest health impact, for example in FCMs.