Life expectancy at birth is one of the most useful indices for measuring the overall level of mortality and estimates the level of mortality more accurately than the crude mortality rate because it is independent of the age structure of the population. It also allows comparing the levels of mortality for different populations in different historical moments. Probabilistic forecasting models generate age-specific mortality rates for future period, and from these results, it is possible to derive forecasts of life expectancy at birth and their corresponding confidence intervals. In this paper two models are applied; the precursor of probabilistic models for mortality: the Lee and Carter model (1992) and the last one proposed in the area: the functional data model developed by Hyndman and Ullah (2008). Both models predict mortality, and enable, through life tables based on mortality forecasts, to derive life expectancy at birth. It is applied to mortality data of Rosario city, in the period 1980 to 2015, so as to obtain point and interval forecasts for life expectancy at birth.