Piezoelectric materials are materials capable of producing an electric current when subjected to mechanical stress. On the other hand, these materials are physically deformed when an electric field is applied to them. In this work, piezoelectrics are used for data acquisition through an acoustic tunnel and thus apply systems identification techniques to the system modeling process. This work aims to identify an acoustic transmission system through black box system identification methods. Specifically, the AutoRegressive with eXogenous Inputs (ARX) and AutoRegressive Moving Average with eXogenous Inputs (ARMAX) linear models and Nonlinear AutoRegressive with eXogenous Inputs (NARX) model with artificial neural network structure are used. This project encompasses all stages of a systems identification process, from data acquisition to results. The results obtained are compared with the ARX model and the ARMAX model. The prediction conclusion shows that the best result was obtained with the ARMAX model.