We present a novel approach in the design of self-care applications aimed at women in pre-menopause and menopause, which is based on the use fuzzy rule-based systems (FRBS) for the description of women's health status, behavior, and personality traits, as well as the provision of adaptive interventions. Our main goal is to develop a personalized solution that informs users and promotes healthy behavioral changes in them, as many women are not conscious of the health consequences caused by menopause. To this end, we follow just-in-time adaptive interventions (JITAI), a design framework for the rule-based provision of personalized and on-demand interventions through mobile applications, according to user's health status and behavior. However, these health-related concepts are usually vague and difficult to formalize in a well-constrained manner. Therefore, to overcome these issues, our approach seeks to leverage the knowledge of health professional experts and the capacity of fuzzy logic modelling and inference to formally define such vague concepts and rules. Although we discuss this approach in the context of menopause self-care, in which prior user data may be insufficient for alternative techniques, it could also be applied in other self-care applications facing similar challenges.