Machine learning has potential in efficiently identifying and modeling microlensing light curves. In this talk, I will present MAGIC, a machine learning method that can efficiently and accurately predict microlensing parameters for binary events. The key feature of MAGIC is its capability to handle irregular sampling, which is common and important to model in current and future microlensing surveys.