The numerous lawsuits in progress or already judged by the Brazilian Supreme Court consists of a large amount of non-structured data. This leads to a large number of hidden or unknown information, since some relationships between lawsuits are not explicit in the available data; and contributes to generate non-intuitive influences between variables, which in addition increases the degree of uncertainty on judicial outcomes. This work proposes an approach to identify possible judgment outcomes that considers the use of similarity calculations and clustering mechanisms based on lawsuits patterns. The similarity problem was tackled by analysing metadata manually extracted from lawsuits; and this work also presents an approach to detect clusters and to compile past votes. From the results, it is possible to verify lawsuits most likely outcomes and to detect their degree of uncertainty.