Drosophila suzukii is a harmful invasive insect pest in global agriculture, causing severe damages and limiting fruit production. It is hidden inside fruits and not visible to the eye during the egg and larval stages, making monitoring and inspection of fruits, thus their trade, extremely difficult. Effective pest management strategies are challenging due to varying population levels, life stage-specific features, and persistence, necessitating the development of precise treatment timing strategies within integrated pest management frameworks. In this thesis, a physiologically based demographic model (PBDM) was chosen and adapted to the population dynamics of the insect in the Italian region of Apulia to setup a forecasting model of D. suzukii. The model identified the insect generation through key features such as development and fertility rates, mortality, longevity, and sex ratio. The model’s forecasting outcomes accurately predicted the biological data of experimental populations, especially at optimal temperatures for insect survival. Data from a one-year survey conducted in the experimental field of CIHEAM Bari were used for the model’s preliminary validation. The results reveal that the model well describes the population dynamics of the insect under experimental conditions. Such results will be useful for developing more effective and sustainable insect monitoring and control methods.