Performance and evaluation measures for clustering algorithms are described in this chapter. We discuss various evaluation measures in order to judge the quality of clustering solutions obtained by clustering algorithms. These measures include cluster validity indices, silhouette coefficients and plots, purity, and others. In addition, we introduce performance profiles to compare efficiency of different clustering algorithms using the accuracy of obtained solutions, the number of distance function evaluations, and computational time.