This paper applies a Ricardian approach to measure the effect of climate change on agriculture performance in Togo using time series data from the period 1971-2004. The findings show that there is a non-linear relationship between agricultural added value and recorded precipitations during the cropping period. More specifically, relatively high precipitation seems to have positive impact on net farm income during the rainy seasons. Marginal impacts are mostly in line with the Ricardian model, showing marginally increasing precipitation during rainy season would increase net farm income, but reduce by the square terms of this season. Climate change impact simulations reveal that changes in climate attributes will reduce agricultural added value. In terms of GDP, climate change will cost Togo a proportion between 2.84 and 6 percent. The authors conclude that adaptation efforts should target more drought-resistant crop varieties and technologies.