Numerous diseases provide challenges to the production of litchi, which can have a significant impact on the crop’s quantity and quality. This paper presents a novel approach to illness prediction by fusing Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs) into a hybrid model. One fully connected layer, three max-pooling layers, and three convolutional layers are all included in the model under study. Extensive experimentation shows that our model performs exceptionally well in properly recognising many Litchi leaf diseases. Combining the best aspects of both techniques, the CNN-SVM hybrid architecture produces a potent feature extraction and reliable data classification capability. The results of our research enhance the progress of precision agricultural techniques, providing farmers with a powerful tool to diagnose and treat diseases in Litchi orchards at an early stage.