Being a clean source of energy, offshore wind turbines (OWTs) are the wave of the future for wind power due to their high efficiency. OWT support structure shares a significant amount in the initial capital investment cost of the OWT farm. Owing to the vulnerability of damage to the support structure from harsh loading and environmental conditions, OWTs are also expensive to operate and maintain, raising the overall energy cost. Checking the structural stability, anticipating potential damages to lower operating costs, scheduling timely maintenance to minimize turbine downtime, and keeping an eye on the system’s state in real time are crucial. The current study provides a critical review of reliability-centric design development for health assessment of the monopile foundation, addressing its challenges and limitations. As an outcome, integrating the reliability assessment with structural health monitoring and condition monitoring is suggested as a solution to existing challenges. Simulating the gathered data with the aid of AI/ML algorithms to calibrate and update the initial reliability model, thereby creating a Digital Twin, will help in the prognostic assessment of the OWT support structure.