Extraction is the process of reducing the number of dimensions being analyzed by a set of variables into a smaller number of factors. In general, extraction of factors proceeds by first extracting the strongest factor that accounts for the most variance, and then progressively extracting successive factors that account for the most remaining variance. We begin this chapter by reviewing a number of key concepts that are essential to understanding EFA, and factor extraction in particular. We then review the different extraction techniques used and the criteria to determine the number of factors to extract.