A chatbot is a piece of software that conducts a conversation with users via auditory or textual methods. A medical chatbot facilitates the job of a healthcare provider and helps improve their performance by interacting with users in a human-like way. There are countless cases where intelligent medical chatbots could help doctors or the patients. They can step in and minimize the amount of time they spend on tasks like providing information to the doctor or guidance to the patient. It’s important to note that even though chatbots can offer valuable facts and symptoms, they aren’t qualified to give an official diagnosis. The main premise behind these talking or texting algorithms, is to become the first point of contact before any human involvement is needed. The objective of the current thesis is the implementation, integration and training of a medical chatbot about Chronic Inflammatory Lung Disease (COPD) in Facebook Messenger. Chatbot will offer the patient an immediate way to be informed for COPD and ways to avoid it. Mainly, a user will be able to do a questionnaire with points, that will inform user about the effect of COPD in its life. If the user completes five questionnaires, chatbot will both offer the user a prediction and will inform him about the biggest improvement of his symptoms or the symptoms that seems to get worse. Chatbot will be trained using the WIT.AI framework in Greek. Wit is a natural language interface for applications capable of turning sentences into structured data. For the implementation of the chatbot’s questionnaire, a MongoDB database in cloud will be used. MongoDB offers limited free storage in the cloud and provide many ways of connectivity like APIs with multiple programming languages or an Analytics application. The connectivity that will support us the most is PyMongo Library, since the whole chatbot will be developed in Python. The framework that will be used for the communication between Python, WIT, MongoDB and Facebook will be Flask. The final application will be built, run and operate in Heroku, a cloud Application Platform. Finally, a Tableau Dashboard will be set up, so that the chatbot’s Administrator will be able to track and monitor each user, provide the Dashboard to the user’s doctor and give the patient custom advices and recommendations.