Statistics are proposed to assist in choosing the number of trees in random forests for classification, one of which is very useful in monitoring of the out-of-bag (OOB) error rate. These statistics are used sequentially as the forest is constructed and are computed from OOB votes or test set votes. They provide a measure of the expected disagreement between the current forest and the limiting forest with infinitely many trees. Examples and simulation studies of the statistic for monitoring of the OOB error rate are provided to illustrate the performance of these statistics.