This paper proposes a methodology to capitalise on the recent advances in technology to efficiently estimate the required condition-related track interventions, possession times and their expected costs for a railway network early in the intervention planning process. Having such estimates not only helps track managers effectively plan and allocate resources, but it also enhances the communication between different stakeholders within the intervention planning process, e.g., asset managers, line planners, capacity managers, and network developers. The methodology uses data of different levels of detail, probabilistic discrete state modelling of the condition of components, and component-level intervention strategies. It also uses fault trees to connect potential losses in service with the likelihood of corrective interventions that may occur due to sudden events as a function of the condition of the components. The methodology is used to estimate the required condition-related interventions, possession times and expected costs for a 25 km railway network in Switzerland. The results indicate that the methodology has the potential to help track managers early in the intervention planning process. Once implemented in a digital environment, the methodology will lead to improvements in the efficiency of the planning process, improvement in the timing of preventive interventions and the reduction in corrective intervention costs.