Introduction Worldwide the transport sector faces several issues related to the rising of traffic demand such as congestion, energy consumption, noise, pollution, safety, etc. Trying to stem the problem, the European Commission is encouraging a modal shift towards railway, considered as one of the key factors for the development of a more sustainable European transport system. The coveted increase in railway share of transport demand for the next decades and the attempt to open up the rail market (for freight, international and recently also local services) strengthen the attention to capacity usage of the system. This contribution proposes a synthetic methodology for the capacity and utilisation analysis of complex interconnected rail networks; the procedure has a dual scope since it allows both a theoretically robust examination of suburban rail systems and a solid approach to be applied, with few additional and consistent assumptions, for feasibility or strategic analysis of wide networks (by efficiently exploiting the use of Big Data and/or available Open Databases). Method In particular the approach proposes a schematization of typical elements of a rail network (stations and line segments) to be applied in case of lack of more detailed data; in the authors' opinion the strength points of the presented procedure stem from the flexibility of the applied synthetic methods and from the joint analysis of nodes and lines. The article, after building a quasiautomatic model to carry out several analyses by changing the border conditions or assumptions, even presents some general abacuses showing the variability of capacity/utilization of the network's elements in function of basic parameters. Results This has helped in both the presented case studies: one focuses on a detailed analysis of the Naples' suburban node, while the other tries to broaden the horizon by examining the whole European rail network with a more specific zoom on the Belgium area. The first application shows how the procedure can be applied in case of availability of fine-grained data and for metropolitan/regional analysis, allowing a precise detection of possible bottlenecks in the system and the individuation of possible interventions to relieve the high usage rate of these elements. The second application represents an on-going attempt to provide a broad analysis of capacity and related parameters for the entire European railway system. It explores the potentiality of the approach and the possible exploitation of different 'Open and Big Data' sources, but the outcomes underline the necessity to rely on proper and adequate information; the accuracy of the results significantly depend on the design and precision of the input database. Conclusion In conclusion, the proposed methodology aims to evaluate capacity and utilisation rates of rail systems at different geographical scales and according to data availability; the outcomes might provide valuable information to allow efficient exploitation and deployment of railway infrastructure, better supporting policy (e.g. investment prioritization, rail infrastructure access charges) and helping to minimize costs for users. The presented case studies show that the method allows indicative evaluations on the use of the system and comparative analysis between different elementary components, providing a first identification of 'weak' links or nodes for which, then, specific and detailed analyses should be carried out, taking into account more in depth their actual configuration, the technical characteristics and the real composition of the traffic (i.e. other elements influencing the rail capacity, such as: the adopted operating systems, the station traffic/route control & safety system, the elastic release of routes, the overlap of block sections, etc.).