The use of early warning system is potential adaptation options to reduce the impact of the climate variability and change.  This study aims to develop a dengue early warning model using climate information.  The model was developed through three steps of analysis.  First step was to determine the length of periods used in prediction and optimal time for eradicating Aedes aegypti mosquito’s breeding sites.  Second step was to identify the best prediction model of dengue incidence rate (IR).  Third step was to develop an early warning model using stochastic spreadsheet.   It was found that the best predictors for predicting dengue incidence rate at week-n (IR_n) were (1) rainfall index with two weeks lead time (ICH_n-2).  The rainfall index of week-n^th is a function of three week moving averages rainfall (CH3), i.e. (CH3_n-1.155*CH3_n-1+0.702*CHn-2), and (2) IR with one week lead time (IR_n-1).  The IR model prediction was IR_n = 0.795*IR_n-1+0.067*ICH_n-2 with R²=76.6%.  These models (result model from first and third step) can be used to provide early warning on optimum time for controlling the mosquito’s breeding sites and the need for fogging action in order to avoid the dengue incidence rate beyond the critical limit defined by the Ministry of Health