Abstract: Method and system for model fitting to hierarchical time series clusters is described. A plurality of time series to be analyzed are clustered as hierarchical time series clusters using Dynamic Time Warping (DTW) as the optimal distance measure to create time series hierarchical clusters. The method disclosed recognizes least dissimilarity time series in the hierarchical time series clusters, and a best fit model is identified for the time series. The same model is continued up the hierarchy along the branch of the hierarchical time series clusters till the model identified satisfies Error Tolerance (ET) and Error Difference (ED) criteria. The method reduces the model fitting time or model building time by more than 50%.