The challenge of recognizing and detecting a novel illness, known as “monkeypox,” is covered in this article. Thousands of people have become ill as a result of the newly found disease’s extensive epidemic, which has even been connected to fatalities. A sufferer may experience the disease’s consequences for as long as three or four weeks. There are currently no such techniques available to analyze the illness. Several deep learning models, including the Monkeypox Skin Lesion Datasets (MSLD), K-nearest neighbor analysis, DenseNet, Naïve Bayes Classifier, and XceptionNet will be used in this study to work on the disease’s identification. These algorithms are trained on images of monkeypox lesion to distinguish them from other diseases, such as chickenpox and smallpox.