over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent developments in the field of mortality forecasts. also, the important feature of this model is that for a precise value of the time index , we can define a complete set of death probabilities that allow us to calculate entries life table. these are some reasons for selecting the lee-carter model in our work. in this thesis we investigate the feasibility of the lee-carter model and two of the main extensions of this model, which are obtained by adding cohort (year of birth) effect, in forecasting mortality rate. we applied these three models on rasht mortality data (total, men and women) in order to find the best model and then use it to forecast rasht mortality rate for the next six years.