classifying divorce cases in iranian judiciary courts using machine learning: a predictive perspective

This study develops a machine learning model to predict the classification of divorce cases in iranian judiciary courts based on socioeconomic factors. using data collected between 2011 and 2018 and various machine learning algorithms, the study evaluates the performance of predictive models through a rigorous 10-fold cross-validation process. results highlight the random forest and neural network classifiers as the most accurate. key socioeconomic factors influencing divorce cases, such as unemployment rate and urbanization rate, are identified. the findings provide actionable insights for policymakers to develop data-driven strategies for social policy and resource allocation.