A leveraging the advanced features of Deep Learning technologies, specifically ResNet for feature extraction and Long Short-Term Memory (LSTM) networks for temporal analysis and prediction, this article provides a comprehensive framework for developing a predictive analytical model for plant health prediction. The model aims to combine spatial features from high-resolution environmental images with temporal environmental data, offering a powerful tool for early detection and prediction of plant health issues