Factor scores have a long tradition within many disciplines, and indeed at one time were very progressive. In some disciplines, they might still be important tools. Thus, we provided this brief chapter. However, we also urge caution in their use. Given what we know about the volatility of EFA analyses (even when the scale is traditionally strong with an unusually clear factor structure), and the conceptual and mathematical issues with factor scores (e.g., controversial mathematical issues like indeterminacy dating back to the early 20th century), individuals wanting to use this technique must be aware of these limitations. It might be useful to attempt to estimate the extent to which factor loadings are volatile or stable (particularly across samples or subgroups), and it might also be useful to consider latent variable modeling (SEM) or modern measurement alternatives (e.g., Rasch, IRT) instead. Rasch analysis, IRT, and SEM have not solved all our problems in measurement, but they might have advantages for some applications. (See also DiStefano, Zhu, & Mindrila (2009.) They are better suited to large samples, but as we hope we have persuaded you by now, EFA should also be a large sample procedure.