Conventional methods of crop yield estimation are often costly, labor-intensive, time-consuming, and prone to inaccuracies due to incomplete field observations. These challenges result in poor yield predictions, limiting farmers’ ability to effectively plan, manage their fields, and optimize production. This project seeks to address these challenges by developing an agricultural yield estimation dataset designed to support the transformation of African agriculture into a data-driven agribusiness. The dataset will enable the development of yield estimation solutions that empower farmers to make informed business decisions. With timely access to key agricultural production data, farmers will be better positioned to plan their harvests, maintain healthy and fresh produce, and ultimately improve their sales and market competitiveness.