We introduce WeHeart, a personalized recommendation device that aims to gradually increase physical activity levels in cardiac rehabilitation. The importance of physical activity in cardiac rehabilitation as a means of reducing associated morbidity and mortality rates is well-established. However, forming physical activity habits is a challenge, and the approach varies depending on individual preferences. Our solution employs a Random Forest classification model that combines both measured and self-reported data to provide personalized recommendations. We also propose to make use of Explainable AI to improve transparency and foster trust.