Abstract: Eucalyptus plantation forests in South Africa have recently been infected by Eucalyptus Snout Beetles. Eucalyptus Snout Beetle, also known as the Gonipterus, feeds on the leaves of the Eucalyptus plantations and can defoliate a tree. A dataset that contains comprehensive information about compartments that are infected by Eucalyptus Snout Beetles and that are not infected was provided. Compartments are separate areas inside a Forest. Exploratory Data Analysis (EDA) techniques were applied on the dataset to find patterns in the data that can help predict Eucalyptus Snout Beetle infections. The aim of this project is to perform modelling based on the insights and patterns extracted from the data through EDA. Classification models were developed in order to classify compartments as a healthy or unhealthy compartment. It was observed that for features such altitude, planted area, frost risk rating and hillslope gradient, there is useful separation between compartments that have been affected by beetles and compatments that have not been affected. There is little or no separation for features such as rotation, time and fell date.