The result of the program encoded into a Genetic Programming (GP) tree is usually returned by the root of that tree. However, this is not a general strategy. In this paper we present and investigate a new variant where the best subtree is chosen to provide the solution of the problem. The other nodes (not belonging to the best subtree) are deleted. This will reduce the size of the chromosome in those cases where its best subtree is different from the entire tree. We have tested this strategy on a wide range of regression and classification problems. Numerical experiments have shown that the proposed approach can improve both the search speed and the quality of results. Categories and Subject Descriptors I.2.6 [Learning]; I.2.8 [Problem Solving, Control Methods and Search] General Terms Algorithms Keywords Genetic Programming, Subtree, Regression, Classification