The safety classification of nuclear power plant equipment serves as the foundation for various management and regulatory requirements related to structures, systems, and components (SSCs). Risk-Informed Safety Classification (RISC) leverages risk insights derived from Probabilistic Safety Assessment (PSA) to optimize the existing safety classification system. This approach helps further enhance resource allocation efficiency in nuclear power plants and improve both the safety and economic performance of the units. This paper investigates the safety classification methods for implicitly modeled SSCs that influence risk insights but are challenging to identify within PSA models, and conducts preliminary pilot analysis on selected SSCs. The research proposes application recommendations for the safety classification of implicitly modeled SSCs based on risk-informed methods, thereby refining the accuracy of domestic RISC approaches and results. Additionally, it provides valuable reference for addressing implicit modeling challenges in other risk-informed applications and PSA model development.