In the present years, climate change due to global warming, resulting in the change of seasons in Indonesia is high variability and unpredictable. Many methods that can be used to predict rainfall pattern, such as parametric regression and ARIMA. However, the model obtained through parametrics statistical approach only concerned to information of samples, therefore, it is poor to interpret the parameters of the rainfall pattern. This study proposes a bayesian nonparametric regression with Gaussian Regression Process approach for rainfall forecasting in the City of Makassar, Indonesia. Based on the value of Root Mean Square Error Prediction (RMSEP), the best covariance function that can be used to forecast is quadratic exponential
