A seasonal outlook for crop insect pests is most valuable when it provides accurate information for timely management decisions. In this study, we investigated the probable relationship between climatic phenomena and pest infestations in Korea using two statistical methods. Brown planthopper was selected because of its migration characteristics, which fits well with the concept of our statistical modelling – utilizing a long-term, multi-regional influence of selected climatic phenomena to predict a dominant biological event at certain time and place. The moving window regression (MWR) model showed high correlation between the national infestation trends of brown planthopper and some tempo-spatial climatic variables near its sequential migration path, while the climate index regression (CIR) model resulted in a relatively low correlation compared to the MWR model. Overall, the statistical models developed in this study showed a promising predictability for rice brown planthopper infestation in Korea, although the dynamical relationships between the infestation and selected climatic phenomena need to be further elucidated.