Tree-based methods are playing an important role in non-linear and non- parametric regression. They have been studied since the 80 s, when the CART algorithm was proposed. Nowadays there is a lot of research in this area and new methods are being created, aiming at improving existing models. This work proposes a new tree-based method called Constructive Regression on Implicit Regions. Its main difference, with respect to other tree-based methods, is how the domain is partitioned. The proposed algorithm allow s partitions formed by flexible regions whose borders are implicitly defined. Moreover, the work also proposes an interval extension to the model. Two different applications of this new method are also proposed. The first one is in actuary , which look s for improvements in the estimation of IBNR reserves, already provided by the usual Chain Ladder model. The second one is in geology , which uses the well data to perform inferences about the missing data in the well itself.