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SUMMARY & CONCLUSIONSReliability plays a pivotal role in the development of high-complexity medical products, which typically take over seven years to reach the market. Despite its importance, system-level reliability often remains unknown during the early and mid-stages of product development due to the unavailability of complete systems and the prohibitive cost of testing. This lack of early visibility can result in significant design changes lately in the development cycle, leading to increased capital equipment costs, delayed timelines, and a substantial rise in post-market warranty expenses. Studies show that these challenges can cause a 40% increase in warranty costs and a twofold increase in component costs for affected parts.To address this critical issue, a predictive reliability modeling approach has been developed to estimate system-level reliability from the earliest stages of product development. The core of the approach involves constructing a Reliability Block Diagram (RBD) using available data, assumptions, and expert inputs, even before the full system design is finalized. Unlike traditional methods that rely solely on field failure data, this approach integrates multiple data streams, including supplier-provided reliability metrics, internal and external test results, early prototype performance, and industry-standard reliability predictions.The reliability model begins with a baseline maturity of 30–50%, offering preliminary insights that support early design decisions. As product development progresses and more empirical data becomes available, the model is continuously refined, reaching 80–90% accuracy by mid-development. Through further testing, feedback loops, and iterative improvements, the model can achieve a final reliability prediction accuracy of 90–96% prior to product release.This methodology enables several strategic benefits:•Early visibility into the system’s critical reliability paths•Proactive planning for corrective and preventive maintenance.•Informed selection of high reliability components.•Optimized allocation of resources and development efforts•Reduced lifecycle and post-market service costs.By shifting the focus of reliability estimation to the front end of the development cycle, organizations can significantly de-risk product development, improve design robustness, and enhance customer satisfaction while reducing overall costs and time to market.