Abstract: In two representative areas of olive oil production in Liguria (northern Italy), we tested the consistency of a degree-day model for predicting the spring emergence of Bactrocera oleae (Rossi) during two consecutive years. We considered that, starting from October oviposition, B. oleae needs to accumulate 379.01 ± 41.264 degree-days for completing its cycle from egg to adult, with a lower threshold of 8.99 °C. We measured the differences between the day of the year predicted by the model for the peak of adult spring flight and that observed in the field. In order to apply Area Wide Pest Management (AWPM) protocols at the regional scale, the model was validated and used to simulate and spatialize the day of adult emergence in spring; the model was tested with the support of software GIS (Geographic Information System) and the regional agrometeorological network of Liguria. Two different spatialization procedures were compared in order to map the model output: geostatistical and regressive. Geographic parameters considered as elements of variability were: elevation, aspect, and distance from the sea. The regressive model provided a more accurate indication of B. oleae behaviour and climate diversity at the local scale than the geostatistical model. The model results were utilized to plan pest-monitoring network at the regional scale.