The rapid proliferation of cyber threats and the increasing sophistication of attacks have created an urgent need for comprehensive cyber threat intelligence (CTI) frameworks that enable proactive detection, effective response, and seamless information sharing. This study presents an integrative examination of contemporary CTI models, focusing on their conceptual foundations, operational applications, and interoperability across organizational boundaries. The paper explores traditional and emerging intelligence frameworks, including the Diamond Model, Lockheed Martin’s Cyber Kill Chain, MITRE ATT&CK, and AI-driven intelligence systems, emphasizing their roles in threat identification, prediction, and mitigation. Additionally, the research evaluates the mechanisms of cyber threat information exchange, the standardization of threat data formats, and the challenges associated with trust, privacy, and governance in collaborative intelligence environments. Using a qualitative meta-analytic approach to synthesize findings from peer-reviewed literature, industry reports, and applied case studies, the study highlights the practical and theoretical implications of integrating advanced machine learning, natural language processing, and anomaly detection methods into CTI operations. The results underscore that organizations leveraging dynamic, predictive intelligence frameworks achieve superior situational awareness, faster incident response, and more efficient containment of malware and advanced persistent threats. The discussion emphasizes limitations in current frameworks, including dependency on data quality, integration complexity, and the human factors influencing threat sharing. Finally, recommendations for future research and practice advocate the development of adaptive, trust-centric CTI platforms capable of real-time analytics and cross-sector collaboration. This study contributes to both the academic and professional domains by providing a robust, theoretically informed, and practically relevant roadmap for enhancing cyber defense capabilities through structured intelligence methodologies.