Computational Quranic studies apply computational methods, mathematical analysis, and cognitive modeling techniques to the study of the Quran. By integrating approaches from computer science, linguistics, data analytics, AI, and cognitive science, researchers explore the structural organization, linguistic patterns, semantic networks, and conceptual frameworks in the Quranic text. Structural modeling examines textual coherence, thematic relationships, and discourse, while mathematical approaches investigate numerical patterns, statistical regularities, and textual features. Cognitive modeling examines how Quranic concepts are processed, interpreted, and retained by readers. As digital humanities expand, Computational Quranic studies offer new opportunities for objective, data-driven analysis that complements traditional scholarship, fostering deeper insights into the text's complexity, organization, and intellectual significance. Computational Quranic Studies: Structural, Mathematical, and Cognitive Modeling introduces a new way of understanding the Quran by treating it as a structured system that can be analyzed, modeled, and understood by intelligent machines. It explores how the Quran can be expressed in the language of data, systems, and AI. This book covers topics such as computational studies, data science, and scripture modeling, and is a useful resource for engineers, mathematicians, educators, religious leaders, academicians, researchers, and scientists.