The Orinoquia is Colombia's last agricultural frontier; although it has become the larder for several cities, agriculture is still rainfed. Furthermore, agricultural producers' weather and climate information decisions are highly uncertain. They are associated with the scarcity of meteorological stations and the extrapolation of weather patterns without objective criteria. Therefore, the first step of this work was to apply a multiplicative bias correction to the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) dataset using 62 in situ rain gauges. The adjusted CHIRPS data were compared with the station records to validate this alternative source of information as a reliable estimator of the average annual rainfall cycle (1983-2022). Subsequently, precipitation was regionalized using the K-means methodology, and each region's annual rainfall cycle was estimated. Finally, the average yearly rainfall cycle determined optimal planting seasons for annual and perennial crops. As a result, the annual and monthly rainfall data from adjusted CHIRPS is good enough to provide accurate data for making agricultural decisions. Based on the rainfall patterns, Orinoquia has five homogeneous regions. The results of this research represent relevant information for territorial and local agrarian planning, and it is one step to becoming a resilient and sustainable agricultural region.