Two reduced rank classification procedures, principal components classification and equal weights classification, are described and compared via a simulation study to the standard classification procedure to determine their feasibilities as alternative classification procedures. First, a justification for the development of these two reduced rank procedures is provided. Then, the two reduced rank rules are derived. The simulation design is described in detail. The simulation results demonstrate that the reduced rank procedures are preferable to the standard procedure under certain conditions (i.e., when they appropriately incorporate prior information about population structure into their classification rules). Suggestions for future research are offered.