Hybrid fiber/coax (HFC) network element and connectivity information in operator databases is sometimes inaccurate, out-of-date, or even missing. Many operational, administrative, and business functions rely on accurate plant data. A solution for programmatically generating coaxial plant topology using Data-Over-Cable Service Interface Specifications (DOCSIS®) network telemetry, spatial and address information, and deployment practices is presented. The approach proposed enables cable operators to keep their system designs up-to-date in real time without relying on manual processes, thereby reducing delays and associated manual burden. By automating the process of map recording, the proposed solution offers significant time savings while ensuring that accurate plant design information is available for efficient field operations, tool development, network planning, and effective service activation and delivery. This approach leverages machine learning (ML) and spatial analysis techniques to extract network topology from DOCSIS network telemetry, deployment practices, and geodata. The effectiveness of the approach is demonstrated through simulations and experiments on real-world data. This solution has the potential to revolutionize how cable operators manage their coaxial plant infrastructure, evolve their networks, and improve overall network efficiency.