Classification of skin disease plays a vital role in early diagnosis and treatment. The correct classification can be more effective in treating the patient for better outcomes. As per the study, machine learning and deep learning methods for skin disease detection, especially the stacking models are proposed. However, with the use of a support vector machine (SVM) and artificial neural networks (ANN), they are trained accordingly with meta-model learning to make the final output. The execution of the models is assessed using multiple evaluation metrics to measure the efficiency and robustness of the skin disease dataset. The model achieves record-level accuracy to highlight diagnostic support.