Globally, the massive expansion of acute respiratory syndrome (COVID_19) is mainly caused by the massive agglomeration of people at the time of travel, as a person infected with the virus who does not have the respective preventive measures can infect 3 more people according to studies. For this reason, here is proposed a mobile application with the use of the Machine Learning methodology for future prediction, through the historical data learned. In this scenario, historical data collection is performed and a decision tree is designed to evaluate the behavior of the data divided into three evaluation criteria (high, medium, and low) probability. As a result, the design of the App is shown with spaces for patient follow-up through, constant chat (doctor-patient), patient communication forums, prescriptions, recommendations and up-to-date information about the virus. This app will be useful for all Peruvian citizens as they avoid mass congestion of people when they move to a health center to have a discard test or other frequently asked questions to a doctor. © 2020, World Academy of Research in Science and Engineering. All rights reserved.