This dissertation develops the Intelligence Hunting Model (IHM), a novel theoretical framework for analyzing how states seek and process bargaining-relevant information. Drawing inspiration from information science, computer science, cybersecurity, and network theory, the IHM posits that intelligence gathering is fundamentally a process of search and inference, shaped by factors such as network structure, signal detection, and belief updating. The dissertation showcases the IHM's versatility through a methodologically diverse set of studies. The first study theoretically explores how the IHM's logic of search and updating can account for catastrophic intelligence failures, using formal model components and qualitative illustrations. An accompanying agent-based model allows for computational experiments. The second study uses a randomized controlled trial, deploying custom-engineered computer systems on the open internet, to analyze state-sponsored cyber operations, modeling them as a search for data within an adversary's network. The third study employs a survey experiment with U.S. business elites, along with statistical analysis, to examine how governments can effectively guide private sector vigilance against espionage by shaping firms' perceptions within a network. Ultimately, this research seeks to foster a more rigorous, theoretically grounded, and empirically driven approach to the study of intelligence, with the IHM providing a foundation for integrating intelligence analysis more centrally within the theoretical debates of International Relations.