Per and polyfluoroalkyl substances (PFASs) are an important class of organic pollutants. Many diverse PFASs are used in commerce and most are not amenable to conventional targeted chemical analysis due to lack of reference standards. Therefore, methods for elucidating the chemical structure of previously unreported or unexpected PFASs in the environment rely extensively on high-resolution mass spectrometry (HRMS). High-throughput structure identification by HRMS is hindered by a lack of PFAS molecular databases and tandem mass spectral libraries. Here, we report a new approach for generating an environmentally relevant PFAS molecular database constructed from curated structure lists and biotic/abiotic in silico predicted transformation products. Further, we have generated a predicted tandem mass spectral library using computational mass spectrometry tools. Results demonstrate the utility of the generated database and approach for identifying PFASs in HRMS-enabled suspect- and nontarget screening studies.