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The problem of conversion of decision tables to decision trees is treated. In most cases, the construction of optimal decision trees is an NP-complete problem and, therefore, a heuristic approach to this problem is necessary. In this heuristic approach, an application of information theoretic concepts to construct efficient decision trees for decision tables which may include "don't care" entries is made. In contrast to most of the existing heuristic algorithms, this algorithm is systematic and is intuitively appealing from an information theoretic standpoint. The algorithm has low design complexity and yet provides near-optimal decision trees.