Predictive Policing combines elements from which two models?

Predictive policing effectively combines statistics and intelligence-led policing, which enhances law enforcement's ability to anticipate crime and allocate resources efficiently. The statistical component involves utilizing data analysis techniques to identify patterns and trends in criminal behavior. This can include crime rates, temporal patterns, and social indicators that reveal areas or times of heightened risk.

Meanwhile, intelligence-led policing focuses on the use of gathered intelligence to inform operational decisions. This model prioritizes actionable intelligence to direct police resources and strategies towards specific crime threats or offenders. By integrating these two models, predictive policing allows law enforcement agencies to leverage data-driven insights and proactive strategies, ultimately aiming to reduce crime through informed decision-making.

In contrast, other combinations may not effectively represent the core principles of predictive policing, as they focus on different facets of policing strategies that do not emphasize the statistical and data-driven nature required for effective prediction and prevention of criminal activities.