This work introduces a predictive BGP security intelligence approach whose core idea is the systematic mapping of Internet routing risk zones — specific ASNs, prefixes, and topological regions of the global BGP graph where routing attacks are most likely to occur and where their impact would be catastrophic if triggered. Rather than focusing on post-incident detection, the proposed concept models the pre-incident attack surface of the global routing system. It analyzes origin-side permissiveness, routing policy structures, inter-AS relationships, prefix characteristics, and global propagation conditions in order to identify where an attack would most probably emerge, how it would propagate, and which parts of the Internet would be affected first and most severely. The central contribution of this work is the conceptual shift from observing BGP attacks after they happen to proactively forecasting high-risk routing zones and likely attack paths before any malicious announcement is made. This mapping enables operators and security teams to prioritize defensive actions based on predicted impact and propagation dynamics rather than reactive incident response. Implementation details, exact scoring formulas, and full source code are intentionally not disclosed, as some components rely on sensitive data and operational intelligence. The contribution of this work lies in defining and formalizing the predictive risk-mapping paradigm for BGP security. Reading Recommendation: Since the files are not organized into folders, it is recommended to start with: Product Overview ASN Vulnerability Metrics — Theory & Security Rationale Prefix Vulnerability Metrics — Theory & Security Rationale The remaining files