Pneumonia could be a life-threatening irresistible infection influencing one or both lungs in people commonly caused by microbes called Streptococcus pneumonia. The hazard of pneumonia is gigantic for numerous, particularly in developing countries where billions confront vitality destitution and rely on contaminating shapes of vitality. There’s a great growing interest within the space of AI for recognizing and classifying images. Chest X-ray (CXR) examination is chosen as one of the foremost ideally for the therapeutic professional for diagnosing pneumonia illness. This research work basically proposes to create utilize of particular varieties of pre-trained CNN models, ML classifiers to gather and distinguish the event of pneumonia illness from a given collection of chest X-ray images.We utilize the Kaggle dataset, to prepare and approve our demonstrate towards the programmed location of pneumonia infection. These inquiries about work seem to offer assistance to the restorative practitioner towards effortlessly distinguishing the pneumonia issue from the X-ray symbolism. Methodologies adopted for the classification task of X Ray images are CNN, Xception, SVM, InceptionV3 models. The model InceptionV3 beats the state-of-the-art in all execution measurements and illustrates diminished inclination and strides in generalization.