Singular spectrum analysis (SSA) is a relatively new and powerful non-parametric time series analysis technique that has demonstrated its capability in forecasting different time series in various disciplines. In this talk, I speak about the feasibility of using the SSA to perform mortality forecasts. Comparisons are made with the Hyndman-Ullah model, which is a new powerful tool in the field of mortality forecasting, and will be considered as a benchmark to evaluate the performance of the SSA for mortality forecasting. We use both SSA and Hyndman-Ullah models to obtain 10 forecasts for the period 2000-2009 in nine European countries including Belgium, Denmark, Finland, France, Italy, The Netherlands, Norway, Sweden and Switzerland. Computational results show a superior accuracy of the SSA forecasting algorithms, when compared with the the Hyndman-Ullah approach.