This study aimed to assess the productive potential of teak plantations in the state of Mato Grosso, Midwest Brazil. We modeled the mean annual increment at the age of 12 years (MAI12) as a function of climatic, edaphic and physiographic variables using artificial neural networks (ANN). The ANNs were shown effective in modeling the mean annual increment, despite of some inconsistences found for areas for which part of the environmental information was not available. The greatest proportion of the land covered by our study (62%) presented moderate productivity, ranging from 10.24 m3 ha-1 year-1 to 28.76 m3 ha‑1 year‑1 MAI12. The highest (MAI12 > 28.76 m3 ha-1 year-1) and the lowest (MAI12 < 10.24 m3 ha‑1 year‑1) productivity areas accounted for 18% and 20% of the study area, respectively. Studies comprising a more comprehensive coverage of the teak production areas are encouraged in order to improve estimation accuracy.