Mental health is a crucial aspect of overall well-being as it affects every aspect of an individual's life, including their thoughts, emotions, and behaviors. A poor mental health could lead to a range of problems, such as anxiety, depression, substance abuse, and even physical health issues. Furthermore, mental health problems could have a significant impact on productivity and social functioning, leading to decreased quality of life and increased healthcare costs. It is crucial to prioritize mental health and take steps to maintain and improve it, such as seeking professional help when necessary and practicing healthy habits. Numerous studies have demonstrated a significant relationship between healthy habits and mental health. Monitoring and registering habits could be beneficial for individuals looking to improve their mental health, for this, tracker apps could be valuable. By tracking their habits and behaviors, individuals could identify areas where they may need to make changes and take steps towards improving their well-being. In recent years, mobile applications have become increasingly popular for monitoring and improving health. Habit trackers, in particular, are apps designed to help establish and maintain healthy habits. Typically, these apps are user-friendly and could provide a wealth of useful information and statistics to help users monitor their progress and stay motivated. However, these apps usually are not focused on mental health. In this project, the aim is to cover this gap by designing and developing a mobile application with habit tracking capabilities that allows users to easily track their habits and moods, with a focus on mental health. In order to accomplish this, the application will use the EMA (Ecological Momentary Assessment) methodology to capture real-time data on user behaviors and moods. This technique involves collecting data over time, through standardized questionnaires that users are asked to fill out at specific times of day or when a relevant event occurs. Such an application enables the monitoring and visualization of the progress not only of habits, but also of moods over time; thus increasing users' motivation and helping them to achieve their goals. The project will be carried out in various phases, which include the analysis of the state of the art, the design and development of the application using the Flutter framework, the realization of a data collection experiment, and finally, the analysis and study of the collected data to identify patterns that promote mental or emotional well-being, using machine learning techniques.