Submarines currently use aging Inertial Navigation Systems (INS) that have demanding maintenance needs. Diagnosing complex problems with critical submarine equipment like the Electrostatically Supported Gyro Navigator (ESGN) Stable Platform and Housing (SP&H) is difficult. A tool that can mine the vast information available from Field Engineer Information Management System (FEIMS) and Level II Manuals, and use smart diagnostics, prognostics and machine learning algorithms to efficiently solve maintenance problems would help optimize the process. IAI and collaborators at The Boeing Company, Integrated Shipboard Systems (ISS), will continue developing the Adaptive Prognostics Tool (APT) system for the Navy. APT will adhere to Naval Open Architecture guidelines and improve maintenance efficiency by presenting accurate and concise troubleshooting recommendations based on text mining historical data of faults and available resources. It will employ a Dynamic Case-Based Reasoning (DCBR) approach, which is a powerful technique for Fault Diagnosis and Prognosis. DCBR allows the accumulation of experience from inclusion of new cases and therefore accommodates learning. APT is a self-learning, adaptive software tool primarily designed for field engineers and Nav ETs to quickly diagnose and provide pertinent repair recommendations. APT will increase mission readiness while also reducing Total Ownership Costs (TOC). This enhanced diagnostic tool will help in many military and commercial applications and can be transitioned into a future SP24 Shipboard Systems Integration Development Program and/or the ESGN Sustainment Program. It would be useful in any advanced system that requires maintenance, in applications such as commercial Autonomous Underwater Vehicles (AUV), industrial machinery, consumer electronics, utility services and remote vehicle diagnostic systems.