As part of the development of a comprehensive strategy for structural equation model building and assessment, a Monte Carlo study evaluated the effectiveness of different exploratory factor analysis extraction and rotation methods for correctly identifying the known population multiple‐indicator measurement model. The exploratory methods fared well in recovering the model except in small sample sizes with highly correlated factors, and even in those situations most of the indicators were correctly assigned to the factors. Surprisingly, the orthogonal varimax rotation did as well as the more sophisticated oblique rotations in recovering the model, and generally yielded more accurate estimates. These results demonstrate that exploratory factor analysis can contribute to a useful heuristic strategy for model specification prior to cross‐validation with confirmatory factor analysis.