Artificial Intelligence Applied to Crime Prediction: A Bibliometric and Systematic Review of Predictive Models, Spatio-Temporal Data, and Emerging Frontiers

Abstract

Crime prediction using Artificial Intelligence has increased in technical complexity and public relevance; however, the evidence remains fragmented regarding implementation practices, publication quality, and scientific collaboration. This paper synthesizes and characterizes the literature on Artificial Intelligence applied to Crime Prediction, with emphasis on development languages, quartile levels, co-authorship networks, and thematic categories.