Optimising the management of a cow with clinical mastitis is crucial for the cow’s welfare, for ongoing milk production and to limit the costs associated with treatment. The purpose of this project is to develop a machine learning underpinned clinical mastitis decision support tool to improve the way in which farmers use antimicrobials on farm. The secondary objective of this project is to substantially improve health event and treatment data capture in the industry’s Central Data Repository (CDR) to enable farm, milk processor and industry level benchmarking of mastitis incidence and antimicrobial use.