This report assesses the economic impacts of climate change on agriculture in Zambia, using the Ricardian method. A multiple linear regression model with net revenue per hectare as response variable has been fitted with climate, hydrological, soil, and socioeconomic variables as explanatory variables. There is one main cropping season in Zambia, lasting from November to April. Crop production in this period depends solely on rains. Considering crop progression in three stages-germination, growing, and maturing, which require different amounts of water and temperature-the climate variables included in the model are long-term averages of the temperature and wetness index for the periods November to December, January to February, and March to April. Assuming a nonlinear relationship of farm revenue with the climate variables, quadratic terms for climate variables were also included in the model. The results indicate that most socioeconomic variables are not significant, whereas some climate variables and the corresponding quadratic variables are significant in the model. Further findings are that an increase in the November-December mean temperature and a decrease in the January-February mean rainfall have negative impacts on net farm revenue, whereas an increase in the January-February mean temperature and mean annual runoff has a positive impact.