In this paper,we consider the design of output layer nodes of multiple linear perceptron network for solving r-class classification problems (r ≥ 3).In general,the output layer is designed in an “ one-to-one” approach.Instead,we will adopt a “binary-coding” approach to build the output layer,which contains q nodes such that 2q-1 < r ≤ 2q with q ≥ 2 and outputs a binary code of the number i if an input belongs to the i-th class.In particular,for multiple linear perceptrons with four hidden nodes,we prove the following result: One-to-one approach can solve an r-class classification problem with r ≤ 16 by using r output nodes,while our binary-coding approach can solve the same problem by using q (q ≤ 4) output nodes.