Decisions in agriculture are made every day that require information to maximise benefit, reduce risk, and increase production or profitability. This demand for information is a driving factor behind the creation of many plant disease models. Models are used to make tactical on-farm decisions, including how and when plant diseases could or should be controlled while also informing high-level policymaking decisions to determine where to focus breeding efforts both geographically and for future investments. Because of the broad range of modelling applications, many different approaches have been used in botanical epidemiology from non-parametric statistical models such as generalised additive models (GAM) to empirical crop growth models with functions for yield losses due to pests and disease. While these approaches are effective in communicating with end-users, often much more impact can be realised by openly sharing the data and code behind the models when it is possible. Recognising this, along with Emerson Del Ponte from the University of Viçosa, Brazil, in 2018 I co-founded Open Plant Pathology, a community of plant pathology, plant disease epidemiology, pathogen population biology, microbial ecology and genomics researchers that supports the several forms of open science practices in plant pathology. I will present a variety of modelling approaches covering a range of crops and diseases that support decision making at scales from in-season sprays to long-term breeding program prioritisations, which need to account for climate change and the possible related changes in plant disease and how and why we should be sharing our data and code.