Cybersecurity has become an unavoidable priority for organizations across all sectors. The increasing sophistication and frequency of cyberattacks, ranging from ransomware to industrial espionage, demand strategic investment in protective measures. However, determining the optimal amount and distribution of this investment poses a complex challenge, where multiple interdependent factors come into play. This research proposes a quantitative methodology based on the Analytic Network Process (ANP) to address this issue. By considering the interdependencies between threats, vulnerabilities, assets, costs, and benefits, the ANP offers a holistic view for decision-making. Through expert judgments, the ANP model enables the prioritization of investments, thus optimizing resource allocation and mitigating risks more effectively. This research reviews relevant literature, formulates hypotheses and specific objectives, and details the proposed methodology, including the application of techniques to mitigate cognitive biases in decision-making. This research is expected to contribute to more informed and efficient decision-making in the field of cybersecurity, strengthening the resilience of organizations against cyber threats.