The regional Mediterranean Fruit Fly Programme (Moscamed) in Belize, Guatemala and southern Mexico has applied geographic information systems (GIS) in the analysis of Mediterranean fruit fly populations since 2004. GIS allow integration of trapping data, control activities and environmental information; when combined with expert knowledge/interpretation (entomologist, ecologist and technical managers), they allow spatio-temporal analysis to determine geographic and temporal patterns, and their relationships with ecological factors and control activities. Ecological factors impacting the distribution of Mediterranean fruit fly (or medfly) populations also allow projecting pest demographics under climate change. Most of the prediction models of climate change indicate that the temperature will increase in the coming years. Temperature is a key ecological factor for insects in general, and medfly is no exception. Auclair et al. (2008) used the climate-host-insect interaction to develop predictive tools related with El Niño Southern Oscillation (ENSO) conditions, under the hypothesis that increasing temperatures will also increase medfly populations. A combination of GIS, statistical analysis, and climate change predictions indicate that hot El Niño years increase the reproductive rate of the pest, whereas cold La Niña years will have the opposite effect. With the medfly prediction model, early warnings can be provided to high-level decision makers and programme managers to act in an effective and timely-manner, including shifting in programme strategies and assigning larger budgetary resources to the programme when expecting difficult years.