A Decision Tree algorithm (DTA) from data is created using construction criteria and considering also the don’t care attributes, for each level of the tree. The DTA goal is to create on-demand a short and accurate decision tree from either data or a stable (or dynamically changing) set of rules. A set of steps provides a decision tree with definite number of nodes and leaves. The pruning of decision rules case is also examined with the consequences on the accuracy. An improved version of DTA (IDTA) provides smaller DT and eliminates branches by using the criterion of less length (CLL).