During the past years, the authors have focused on the development of an Integrated Probabilistic Risk Assessment (I-PRA) methodological framework to increase the realism of fire risk analysis for Nuclear Power Plants (NPPs). In 2019, an academia-industry collaboration project was initiated to expand the Fire I-PRA research to a full-scope NPP. In the first phase of this project, a screening process was required to find critical fire scenarios that could benefit the most from a detailed analysis using the Fire I-PRA methodological framework. This paper reports on the progress of the first phase of the project focusing on advancements of the screening process for Fire PRA. The Risk-Informed over Deterministic (RoverD) screening methodology is introduced to gradually improve the Degree of Realism (DoR) and guide the screening process based on the estimation of risk and the associated cost (e.g., cost related to the required data collection for advancing DoR). The RoverD methodology is based on utilizing a blend of deterministically and risk-based elements to demonstrate compliance with the regulatory requirements. This study discusses a spectrum of DoR in the screening process of risk-informed applications where the DoR is gradually and efficiently increased. Although the RoverD methodology is applicable for divers risk-informed applications, this paper covers its implementation for Fire PRA. In the case study, two fire modeling approaches (i.e., engineering correlations and zone models) are used to investigate the impact of improving the DoR in the screening process, specifically advancing the DoR in the Zone of Influence (ZOI) of fixed ignition sources.