In this paper, the problem of forecasting a time series with only a small amount of data is addressed within a regression method. The procedure works well when standard methods cannot be applied due to the reduced number of observations. The quantity to be predicted is the accumulated value of a positive and continuous variable for which partially accumulated data are available. A very simple model is proposed to describe the relationship between the partial and total values of the variable to be forecasted under the assumption of stable seasonality. These conditions appear in a natural way in the prediction of seasonal sales of style goods, such as toys or banking deposits, among many other examples.