The prevalence of various health conditions in women highlights the urgent need for effective disease prediction strategies. This paper delves into utilizing Artificial Intelligence (AI) for early disease prediction in women, focusing on prevalent conditions. Through large-scale datasets and an advanced machine learning algorithm, predictive models can identify high-risk individuals before symptoms emerge. The methodology covers data preprocessing, feature selection, and model development, showcasing AI’s role in risk stratification and targeted prevention. Ethical considerations are explored, stressing fairness, transparency, and privacy in model deployment. Socio-economic factors’ impact on AI-driven predictive tools’ accessibility and effectiveness is discussed, advocating for equitable healthcare delivery. This research underscores AI’s potential to transform early disease prediction, enhancing healthcare outcomes and women’s well-being within the evolving landscape of precision medicine.