Globally, there are serious health hazards associated with bone illnesses such osteoporosis, osteoarthritis, and bone cancer. For management to be effective, prompt action and precise detection are essential. Using deep learning techniques to diagnose bone diseases in images of osteoporosis, osteoarthritis, and bone cancer is examined in this study. This model classifies different bone diseases using convolutional neural networks (CNN), VGG16, Densenet, and Inception. By recognizing disease specific patterns in various bone diseases, this model which was trained on an x-ray image dataset allows for precise diagnosis and customized recommendations. According to preliminary findings, deep learning models perform better in terms of disease type detection accuracy than traditional techniques. For this bone disease detection CNN performed well with an accuracy of 0.9757.