With increasing population and developing technology in the world, electric vehicles are taking the place of traditional transportation vehicles dependent on limited fossil fuels. Rapid increase in the number of electric vehicles and charging station loads challenges the adequacy and reliability of distribution networks. Since it is not possible to estimate demanding power of electric vehicle charging stations on an hourly or seasonal basis, it has been shown in this study that probabilistic future projections can be made taking into account the measurements of the past years and effects of electric vehicle charging stations on the distribution network's reliability indices (SAIDI, SAIFI) are investigated for these future projections. Topology of distribution system and measurement data used is based on a local distribution network's statistics and measurements. Probabilistic modelling approach used in this study includes usage of the Probability Density Function (PDF) of Weibull distribution, Latin Hypercube Sampling (LHS) method, correlation between the loads and generation of optimum scenarios by applying re-ordering algorithm (ROA) in the context of suitable correlation between loads.