Marriage is a physical and spiritual bond between a man and a woman as husband and wife, with the aim of forming a happy and lasting family based on belief in God Almighty. Premature marriage can have adverse effects, not only for the husband and wife, but also for future generations. The utilization of machine learning is needed to analyze the potential risk of early marriage. To date, programmatic and research approaches to marriage age maturity have primarily relied on inferential statistics, with limited application of machine learning methods.This study aims to develop a decision support system for promoting marriage age maturity among adolescents in East Java. This is a non-reactive study utilizing secondary data from the 2018 SKAP (Survey on Family Planning Performance and Accountability), obtained from the East Java Representative Office of BKKBN. The unit of analysis is all adolescent respondents in East Java who met the criteria for participation in the 2018 SKAP. Data analysis was conducted using univariate, bivariate, and Decision Tree methods. Knowledge was found to be a complex factor influencing adolescents' decisions regarding marriage planning, while economic status emerged as an additional supporting factor. The results of the machine learning analysis, presented in the form of an algorithm, are expected to serve as a foundation for decision-making related to the promotion of marriage age maturity among adolescents in East Java. Keywords: Adolescents, decision tree, marriage