Tree height measurement is one of the most difficult activities in forest inventory data gathering, although it is a fundamental variable to support forest management, since it is an input for modelling growth and yield. To overcome this obstacle and ensure that the heights of trees are estimated accurately, hypsometric relationships are used. Therefore, the objective of this study was to compare different fitting strategies (i.e. nonlinear least squares and mixed-effects) to predict tree height in African mahogany Brazilian plantations using well know local (using only tree height and diameter) and generalized (using height, diameter and plot level variables) models. Data were gathered on 149 permanent plots sampled in different Brazilian regions and ages, totaling 4,201 height-diameter pairs. Different models were evaluated and the best method to estimate the height-diameter relationship was based on statistical and graphical criteria. A local model using mixed-effects with correction of heteroscedasticity was efficient and superior to other models evaluated. However, when using an independent data base, the generalized model fitted by nonlinear least squares generates adequate results that are scaled to the plots’ productivity, since the inclusion of dominant height into the model helps to predict height locally.