In this thesis the problem of the combination of binary classifiers ensemble is faced. The combination of different experts is currently investigated by researchers to increase the reliability of the decision. Thus in this thesis the following two aspects are investigated: a score “selection” methodology, and diversity measures of ensemble effectiveness. In particular, a theory on ideal score selection has been developed, and a number of selection techniques based on it have been deployed. Moreover some of them are based on the use of classifier as a selection support, thus different use of these classifier is analyzed. The influence of the characteristics of the individual experts to the final performance of the combined experts have been investigated. To this end some measures based on the characteristics of the individual experts were developed to evaluate the ensemble effectiveness.