In Colombia, the oil palm industry faces challenges due to its geographical extension in 161 municipalities and the participation of small-scale farmers. The lack of adequate monitoring increases vulnerability to pests and adverse conditions, generating economic losses. SIMOPALMA's proposal uses deep learning and satellite image analysis to offer a comprehensive solution. It implements CNN models in ArcGIS Enterprise, enabling automated identification and health analysis of oil palms. The project, divided into requirements specification, design, implementation and validation phases, highlights the efficiency and scalability of SIMOPALMA for crop management, providing an objective and beneficial perspective for sustainable agricultural practices.