Jump-diffusion models have been suggested to fit most interest rate processes. The aim of this thesis is to propose a procedure for forecasting the interest rate and pricing the options based on it. This procedure, considering of detecting possible jumps and relating them with economic and monetary events, is applied to the Fed funds rate and 3-month T-bill rate processes. It is seen that the proposed Gaussian-Poisson-event model fits both series better than the pure Gaussian model does. Also seen is there are more jumps in the Fed funds rate than in the yield, a result that is due to the direct impact of the Fed events to Fed funds rate. Empirical studies show that the information about jumps is helpful for the pricing of the interest rate options.