There are hundreds of mobile apps for smoking cessation but many of them are designed without clear evidence or the use of behavioral change models. In this presentation, we will explore how data-driven recommender systems can be used to create mobile behavioral interventions that adjust to the context of the patients in a more automatic and user-friendly manner. We will explore how we can combine the field of tailored health education with data-driven recommender systems which are delivered using mobile technologies. This presentation will use a study case the mHealth solution for smoking cessation developed in the project SmokeFreeBrain with combines just-in-time motivational messages based on the i-Change behavioral change model.