Drought is a severe, recurrent disaster for Mexican agriculture, causing huge economic losses, which could be reduced if appropriate planning and policies were carried out and the production loss could be predicted. This paper presents the application of a genetic programming scheme to obtain normalized curves of annual agricultural production for each state in Mexico as a function of the return period of drought events and, from them, compute the normalized value of the yearly production. This value, multiplied by the historic mean production of the state, gives the production expressed in Mexican pesos for a specifi ed return period. Two techniques were used for this data analysis, the fi rst one is general and considers each state separately; for the second technique the country was divided into six groups, depending on the value of the agricultural production variation coeffi cient. The results showed that for the ficase large dispersion was found between the reported and computed data, while a better fi