In our daily life, we face all kinds of situations and problems, which directly affect us and alter our moods. One of the most common things that have become almost completely integrated into our lives without us even realizing it, is music. On the street, in the car, at a restaurant, or at home, it is present in our lives. Music has become for many people a method of therapy, a way to temporarily escape from the space in which we are captive, and a way to block out any outside sound in order to find our inner peace and be able to have a few moments of introspection, undisturbed by events external to us. Music listeners often find themselves in a situation where they open a music app and receive a list of recommendations that didn't match their mood. Thus, we considered that an application that at least tries to provide recommendations that consider this aspect could be helpful. For this, we built a music application that has a component to detect the emotion experienced by the user in order to offer suggestions as personalized as possible.