We derive the best predictive estimator (BPE) of the fixed parameters under two well-known small area models, the Fay-Herriot model and the nested error regression model. This leads to a new prediction procedure, called observed best prediction (OBP), which is different from the empirical best linear unbiased prediction (EBLUP). We show that BPE is more reasonable than the traditional estimators...