Scientists from the Pacific University have developed a neural network to predict crop yields in the Khabarovsk region. With an accuracy of 85%, it determines the productivity of various crops in fertile soil using meteorological data, satellite imagery, and soil characteristics. The model obtained will help agronomists optimize resources and reduce risks. Scientists plan to refine the neural network to increase accuracy and expand functionality.