There is a demand for the improved safety and economics of advanced nuclear energy systems. The world's first high-temperature gas-cooled reactor pebble-bed module nuclear power plant (HTR-PM Demo Project) is about to be completed in China. This power plant achieved initial full power at the end of 2022. The success of the HTR-PM Demo Project shows the importance of risk-informed initiatives throughout the project with solid support from comprehensive risk assessment. This paper focuses on a technical issue that needs to be solved when conducting risk-informed initiatives for HTR-PM, namely the issue of reliability data for first-of-a-kind (FOAK) equipment. In short, no data for the FOAK equipment are available in existing reliability databases. On the basis of the HTR-PM pilot experience, this paper proposes a process of estimating the required data for the reliability parameters of FOAK equipment. The process has five steps: (1) identification of key parts and assemblies, (2) preliminary determination of the reliability parameters and the associated reference values for the key parts and assemblies, (3) analysis of maintenance management tactics, (4) estimation of reliability parameters for the FOAK equipment using a Bayesian network, and (5) Bayesian updating with operational data. The helium circulator of HTR-PM is taken as an example to demonstrate the feasibility of the proposed process. A lack of reliability data is a common issue for innovative nuclear energy systems. The proposed process is supposed to be universal to all types of innovative design.