Atmospheric discharges are of great importance to power systems, and are often responsible for outages of transmission lines, which can trigger a sequence of events that leads to a system collapse. The long extensions of transmission lines, exposed to climatic conditions, create significant probability of direct incidence of atmospheric discharges in these equipments. Due to the strategic nature of power supply lines and the fact that atmospheric discharges are among the main causes of outages, it is important to study atmospheric discharges characteristics before failure of transmission lines and understand patterns that are responsible for interruptions. Current studies focus on efficiency of lightning detection networks and on identification of climatic conditions that indicate lightning occurrence in a predictive approach, without any correlation with transmission lines outages. Therefore, this thesis consists on real-time risk determination of transmission lines outage by lightning, providing early information to enabling operational procedures for power system safety. The proposed model, named Transmission Lines Outage Risk by Lightning (TLORL) is composed of two main modules: Atmospheric Discharge Data Clustering and Classification. In the atmospheric discharges data-clustering module, performed by a density-based method, the outages are efficiently eliminated and representative groups of atmospheric discharges are formed. The second module consists of a classification step, based on artificial neural networks, to identify patterns of discharges groups that represent risks to cause transmission lines outages. Aiming at improving the proposed model, principal components analysis (PCA) was applied to determine the input variables that most contribute to the events characterization. The TLORL model was tested with real data transmission line outages, associated to another database with millions lightning records from the detection networks, producing excellent results of transmission lines outages caused by atmospheric discharges.