Gridded data of precipitation are a valuable tool in scarce-observational data contexts. Validation through statistical analysis is essential for its use. This work aims to validate the Climate Hazards Infrared Precipitation with Stations (CHIRPS) database for the southwest of Buenos Aires province over the period 1990-2020. This dataset has adequate spatio-temporal coverage to study rainfall variability since it presents daily and continuous coverage from 1980 to the present with a resolution of 0.05 degrees between 50 degrees S and 50 degrees N. For validation purposes, Pearson's correlation coefficient (r-Pearson), mean absolute error (mae), root mean squared error (rmse) and percent bias (pbias) were applied in the R environment using the hydroGOF package. CHIRPS shows a correlation between 0.68 and 0.84 for observed data on both monthly and annual scales. It also tends to overestimate rainfall between 2 and 4%on a monthly scale, except in the northwestern sector, where it was underestimated between 4 and 11%. At the annual scale, overestimation was between 3 and 4%, while underestimation presented the same characteristics as at the monthly scale. The analysis of mae and rmse showed greater errors in the stations near the mountain range at both time scales. It is concluded that CHIRPS is applicable for rainfall variability studies in the analyzed region, where the lack of data is a recurrent problem, considering the spatial errors detected.