We applied two methods to assess vulnerability to climate change in Mexico’s agricultural sector. The first one was a principal component analysis (PCA) that weighted each variable separately. For the second one, we integrated the variables in a linear array in which all variables were weighted equally, and then, we used the arithmetic sum of the sub-indices of exposure and sensitivity minus the adaptive capacity to obtain the vulnerability index. We discuss the similarities and differences between two methods with respect to municipal-level maps as the outputs. The application of the method for the agricultural sector in Mexico gave us the spatial distribution of the high- and very-high vulnerability categories, which we propose as a tool for policy. The methods agreed that the very-high vulnerability category is present in 39 municipalities. Also we found that 16 % of the total population in the country is located in high-exposure areas. In addition, 41 % lives in municipalities identified as highly-sensitive. In terms of adaptive capacity, 20 % of the population lives in 1273 municipalities with low-adaptive capacity. Finally, we discuss the need for information regarding vulnerability at the national level to guide policies aimed at reducing exposure and sensitivity and increasing adaptive capacity.