Abstract: FABI operates a disease clinic program that offers services to the industry. These services include identification of pathogens and pests that affect the industry and provide advice on how to manage them. These service accumulated data about the occurrence of pathogens and diseases over the past 25 years. In addition, the Institute of Commercial Forestry Research (ICFR) holds GIS database that include various variables that can be linked to provide industry with data that can assist in planning, managing and preventing future outbreaks of these pests and diseases. The purpose of this project is to Clean and Integrate FABI and ICFR datasets and use the data to design machine learning models which can be used to perform pre-diagnosis of new samples to predict plant pests and diseases.