Low income households, especially in the developing countries such as India could suffer losses due to weather related events such as drought, hurricanes, floods etc. Such losses could cast a household into a chronic poverty cycle - a poverty trap from which the household may find it difficult to re-emerge. Rainfall derivatives are the insurance contracts that compensate a household based on the weather outcome rather than the actual crop yield. Traditional methods for pricing rainfall derivatives include burn analysis, index value simulation and daily rainfall simulation. In this work, we price the rainfall derivatives using a different method that uses the Gaussian and t copulas to capture the dependence between the monthly rainfalls in the monsoon season in India. We find that though the premiums calculated using burn analysis and our proposed method were equal, the standard deviation and Value at Risk “VaR” of the insurance payoffs calculated using both the methods differed. Therefore, in practice, the actuarial pricing of the rainfall insurance contract using burn analysis and our proposed method could be different. Our method could be easily applied to price rainfall derivatives for the regions that exhibit extreme rainfall patterns.