Abstract: A new separability-based inductive learning algorithm is proposed in this paper. The algorithm is different from existing inductive learning algorithms. Starting directly from the separability of features for different classes, building a separability criterion, then forming a decision tree, the algorithm can classify rnulticlass concepts. The algorithm is intuitive, simple, and convenient for computation. Its effectineness is illustrated by an example in this paper.