Abstmf-This paper proposes a methodology and a practical tool for the study of long-term network planning under uncertainties. In this approach the major external uncertainties during the planning horizon are modeled as macro-scenarios at different future time instants. On the other hand, the random nature of actual operating conditions is taken into account by using a probabilistic model of micro-scenarios based on past statistics. Massive Monte-Carlo simulatiuns are used to generate and simulate a large number of scenarios and store the detailed results in a relational database. Data mining techniques are then applied to extract information from the database so as to rank ~renario~ and network reinforcements according to different criteria.Index Terms-Data Mining, power systems planning, probabilistic methods, random sampling.