Antimicrobial resistance (AMR) poses a significant threat to public health, driven by the widespread dissemination of AMR genes between microorganisms via mobile genetic elements. Current phylogenetic models rely on vertical inheritance and chromosomal variation, which do not track mobile antibiotic resistance genes, such as blaKPC, effectively. This project aimed to develop a novel analytical framework to trace the recent evolutionary history of blaKPC. The TETyper pipeline was run on a globally distributed dataset of 5286Illumina bacterial whole-genome sequences containing blaKPC and used three common blaKPCcontexts as references: Tn4401, Tn4401-Tn2, and NTEKPC. The pipeline analysed variation relative to a given blaKPC context reference for each isolate sequence to build phylogeneticnetworks, with nodes defined as TETyper profiles and edges drawn based on distancesderived from these profiles. Networks were developed using four distance measures for each reference: SNPs, deletions, and flanking regions, as well as a measure combining the three. Metadata regarding taxonomy, country, and year of isolation was also overlayed on the networks via node colouring. Overall, these networks captured variation in blaKPC genomic context while displaying potentially informative trends between references and measures. Building on this, smaller outbreaks of KPC-producing bacteria have been used to refine the model, looking to incorporate epidemiological data to retrospectively delineate transmission networks. Despite some limitations in the methodology (i.e. inaccuracies in the recognition ofvariation in Tn4401-Tn2 and biases when overlaying metadata and profile nodes), theframework enables a detailed characterisation of blaKPC mobility and evolution. This work provides a proof of concept for modelling mobile gene evolution based on variation in genomic context.