The use of multi-layer perceptrons (MLP) to determine the significance of climatic variables to the establishment of insect pest species is described. Results show that the MLP are able to learn to accurately predict the establishment of a pest species within a specific geographic region. Analysis of the MLP yielded insights into the contribution of the individual input variables and allowed for the identification of those variables that were most significant in either encouraging or inhibiting establishment.