A classifiers ensemble approach based on Principal Component Analysis (PCA) was proposed. Lots of original classifiers were got from Random Subspace Method (RSM). According to their classification performance, their preservation scores were given, so the preferential ranks for classifiers preservation were ordered, by which a set of classifiers was selected from original classifiers. Theoretic analysis and experimental results in face database ORL show that this pattern classification method based on ensemble PCA is efficient for pattern recognition.