This research investigates marriage trends in Malaysia using open data from the Department of Statistics Malaysia (DOSM), with a focus on understanding historical patterns, forecasting future marriage rates, and exploring potential intervention strategies to mitigate the negative impacts of an aging population and low birth rates. Employing a combined approach of exploratory data analysis and machine learning, we aim to analyze historical marriage patterns and forecast future trends. The exploratory analysis examines marriage data by age, gender, and state, revealing demographic patterns and potential influences of socioeconomic and cultural factors. Building on these insights, we develop and evaluate machine learning models, incorporating socioeconomic and demographic indicators, to forecast marriage rates. Our findings highlight the influence of population density and income on marriage rates, forming complex feedback loops. This research contributes to a comprehensive understanding of marriage dynamics in Malaysia, offering valuable insights for policymakers and researchers interested in marriage trends, their societal implications, and potential interventions to address demographic challenges. The study acknowledges limitations in data availability and model accuracy, particularly for long-term forecasts.