Data insufficiency is one of the main challenges faced in hydrological studies, including a lack of knowledge regarding flow duration curves (FDCs). Thus, homogeneous regions of streamflow were identified in the Amazon using the Fuzzy C-Means (FCM) method. The PBM index was used to validate the clustering obtained via FCM, in turn, a homogeneity test based on the L-moment was applied to confirm the homogeneity in each defined region. Linear, power, exponential, logarithmic, quadratic and cubic mathematical models were fitted to the FDCs observed in the homogeneous regions. The models are the result of multiple regression analyses involving the parameters of the fitted FDC and the physico-climatic characteristics of the watersheds. The models were validated using the Jack-knife cross-validation method. The validation was satisfactory, with NASH coefficients higher than 0.50. Additionally, the standard deviation (RSR) of observations was less than 0.70, and the averages of the relative mean square error did not exceed 12.26%. These results are relevant for 89.91% of the analyzed watersheds and 73.58% of the study area. Thus, FDCs may be estimated in large parts of the Amazon, thereby making the methodology presented a valuable tool to support projects involving the planning and management of water resources.