Chemical attribution signatures (CAS) can be used to obtain useful forensic information and evidence from illicit drug seizures. A CAS is typically generated using hyphenated chemical analysis techniques and consists of a fingerprint of the by-products and additives present in a sample. Among other things, it can provide information on the samples origin, its method of production, and the sources of its precursors. This work investigates the possibility of using multivariate CAS analysis to identify the synthetic methods used to prepare seized fentanyl analogues, independently of the analogues acyl derivatization. Three chemists working in two labs synthesized three different fentanyl analogues, preparing each one in duplicate by six different routes. The final collection of analogues (96 samples) and two intermediates (16 + 32 samples) were analysed by GC-MS and UHPLC-HRMS, and the resulting analytical data were used for multivariate modelling. Independently of analogue structure, the tested fentanyls could be classified based on the method used in the first step of their synthesis. The multivariate models ability to classify unknown samples was then evaluated by applying it to six new fentanyl analogues. Additionally, seized fentanyl samples was analysed and classified by the model.