Abstract

This chapter explores how predictive analytics is transforming public administration from reactive to proactive, citizen-centered governance. It examines how governments can use historical, real-time, and multi-source data—such as demographic, health, infrastructure, and social media information—to anticipate societal needs and intervene early. Drawing on welfare and public health examples, it demonstrates how predictive models support timely detection of service demands, risks, and policy gaps, enhancing operational efficiency and crisis management. The chapter also addresses ethical and regulatory challenges, including algorithmic accountability, data privacy, and transparency. By emphasizing AI, digital twins, and real-time analytics, it offers a data-driven framework for building inclusive, responsive, and future-ready governance systems.