The precipitation forecast is the primary link in rainwater potential calculation. However, there is a high degree of uncertainty and randomness in precipitation process, it is difficult to determine the exact value of the precipitation in certain period of time with physical methods.Therefore Markov model can be used to predict based on probability theory and random process theory through using the method of weighted and sliding average treatment of precipitation sequence so as to reduce the randomness of the sequence and improve the prediction accuracy.Case study made the analysis of Jianyang precipitation data from 1953to 2004in which application of precipatition data from 2006to 2009was used to to do model checking. Therefore, model predicts applying this model of annual precipitation from 2010to 2015was done. The results shows that precipitation forecast is feasible applicating weighted moving average Markov prediction model. And the method is meaningful with simple calculation and high prediction accuracy.