## 6 Conclusions  
To maximize the safety of a railway system, it is necessary to identify tools capable of identifying, analyzing, and controlling the main hazards and preventing accidents. This is even more true in LCs, where the normal risks of a railway are added to factors of randomness related to the interaction with the road system. To this end, this work describes a quantitative Risk Management framework capable of assessing the risk level of level crossings and presents its application as a tool to support the decision-making process for the management and improvement of the safety level. In particular, the methodology is described in all its steps, from the system definition phase to the risk acceptability and treatment. The application to 96 LCs of an Italian narrow gauge local railway is presented. All the necessary data were collected, and the LCs were characterized according to their safety protection systems. The available data made it possible to quantitatively assess the causes and consequences of all accidental scenarios for all LCs through the application of the FTA and ETA methodologies. Each scenario was characterized by its relative frequency and severity, making it possible to calculate the Individual (IR) and Cumulative (CR) Risk levels. The risk indicators were then compared with the relative acceptability and tolerability thresholds, identifying the LCs at acceptable risk and those in the area of attention for which any mitigating barriers must be assessed. Then, for a level crossing with a risk level in the attention area, the use of the framework as a tool to support decisions was described, evaluating the effect on the risk of three different possible interventions to make the LC safe. Additionally, the framework is not limited by geographic boundaries and can be adapted for use in railway systems worldwide. Provided that relevant local data--such as traffic conditions, safety systems, and environmental factors--are available, the RM framework can be effectively tailored to various national contexts. Its flexible structure enables it to accommodate different types of rail systems and crossing characteristics, making it a universal tool for improving LC safety. In conclusion, the methodology presented in this work, especially if combined with GIS tools, is able to highlight the effect of changes both to the single LC and to the network. From the perspective of level crossings (LCs), the tool identifies high-risk 'black spots' and highlights the specific risk factors that need mitigation. On a broader network scale, it enables the evaluation of decisions such as changes in train speed or modifications in the number and type of trains, offering an immediate overview of how these adjustments affect the overall risk levels. By applying the methodology iteratively within a cost-benefit analysis, the effectiveness of each mitigation measure can be assessed, allowing for a clear prioritization of interventions and helping to identify the most cost-effective solutions. Finally, when integrated with additional non-quantitative factors--such as user comfort and environmental impact--within a Multi-Criteria Decision Analysis framework, the results of the RM process can provide comprehensive and reliable insights to support decision-making across the system. Conceptualization, A.D.G. ; Methodology, A.D.G. and V.M. ; Formal analysis, V.M. ; Writing--original draft, V.M. ; Writing--review & editing, A.D.G. ; Supervision, A.D.G. All authors have read and agreed to the published version of the manuscript. This work has also been partially financed by the University of Catania within the project TIMUC \"Piano della Ricerca Dipartimentale 2018-2020\" of the Department of Civil Engineering and Architecture. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.