Violence against women (VAW) is an urgent problem that not only has severe physical impacts but also psychological impacts. Predicting violence based on its type increases efficiency, accuracy, and early detection. This ensures that prevention, intervention, and policies can be more targeted and focused, as interventions for each type of violence vary and require a tailored approach. This study aims to develop the latest prediction model to predict VAW in each type which were physical, psychological, economic, and sexual violence. The methodology used is machine learning with the naive bayes, random forest, and logistic regression algorithms because it provides a balance of efficiency, ease of interpretation, and the ability to handle complex data often encountered in the context of predicting VAW. A representative research sample of 600 married women, data collection through questionnaires designed to capture variables and characteristics associated with various types of VAW. The desi.....

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