AI-Driven Predictive Modeling of Marriage Rates in Nigeria: Analyzing the Roles of Tradition, Education, Age and Socioeconomic Status

Ugwuja; Nnenna Esther; Omankwu; Obinnaya Chinecherem Beloved

doi:10.56201/ijcsmt.vol.11.no7.2025.pg13.24

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AI-Driven Predictive Modeling of Marriage Rates in Nigeria: Analyzing the Roles of Tradition, Education, Age and Socioeconomic Status

Ugwuja, Nnenna Esther and Omankwu, Obinnaya Chinecherem Beloved

Abstract

This study presents an AI-driven approach to predicting marriage rates in Nigeria by analyzing the influence of socio-cultural and economic factors. Despite the central role marriage plays in Nigerian society, existing literature provides limited insight into how tradition, geopolitical zones, age, physical attractiveness, educational attainment, family background, and employment status collectively affect marital trends. This research applies supervised machine learning techniques— including logistic regression, decision trees, and random forest classifiers—to develop predictive models based on demographic data and survey responses. The analysis reveals that age, educational qualification, and employment status are the most significant predictors of marriage likelihood. Traditional norms and regional affiliations also contribute substantially, though their influence varies across Nigeria’s geopolitical zones. The study underscores the value of artificial intelligence in modeling complex social phenomena and offers a replicable methodological framework for social forecasting in diverse cultural settings. The findings have practical implications for policymakers, sociologists, and religious institutions seeking data-driven insights into marital behavior, and highlight the transformative potential of AI in interdisciplinary social research.

Keywords

Artificial IntelligenceMarriage RateNigeriaSociocultural FactorsPredictive

References

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AI-Driven Predictive Modeling of Marriage Rates in Nigeria: Analyzing the Roles of Tradition, Education, Age and Socioeconomic Status

Abstract

Keywords

References

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