Pneumonia being one of the most concurrent prevalent lethal diseases, is responsible for several thousand deaths every year. X-rays images are commonly used to make clinical diagnosis for pneumonia but are not as revealing as MRIs or CT scans and the diagnosis is prone to be erroneous. Trained models help to make an accurate and more reliable computer-aided diagnosis of Pneumonia based on the X-ray images of lungs. In order to evaluate the Sigmoid-function, which is a variant of Transfer Learning, a Convolutional Neural Network/ VGG19 layer is used to achieve good performance. The problems and potential enhancements with the model of Transfer Learning is also used and discussed. Pneumonia Detection application user able to input the X-ray images and able to view the result whether the patient has suffered from Pneumonia or not. It shows expected result for proper X-ray images within the scope of the system. Error messages were shown when required. Time taken was moderate for moderate sized images. Excessive delays were not encountered the final accuracy obtained was 86.388 %.