This paper discusses the idea and the design of an automated system for storage and management of mycotoxins reports for decision making. Mycotoxins are poisonous chemical compounds produced by certain fungi. Mycotoxins are fungal secondary metabolites that contaminate various feedstuffs and agricultural crops. The contamination of food by mycotoxins can occur before production, during storage, processing, transportation or marketing of the food products. High temperature, moisture content and water activity are among the factors that facilitate the production of mycotoxins in food. The five major mycotoxins produced in food and feedstuffs are Aflatoxins, ochratoxins, fumonisins, deoxynivalenol and zearalenone. In Africa, mycotoxin contamination is considered to be a major problem with implications that causes human and animal health hazards and poor economy. Aflatoxin-related hepatic diseases are reported in many African countries. Ochratoxin and fumonisin toxicity in humans and animals is widespread in Africa. The available and updated information on the incidence of mycotoxin is not collectively vivid for policy making. A complete automated system allows to monitor the statistical report of mycotoxins stored in agricultural products. This study involves analytical Service conducted on Mycotoxins such as Mold Culture and Identification and Chemical Analysis which involves microbiological Culturing; Microscopic or biochemical identification, enzyme linked Immunosorbent (ELISA), tin layer Chromatography (TLC), high Performance Liquid Chromatography (HPLC), and gas Chromatography /Mass Spectroscopy. The design and development of Mycotoxins Automated Database System (MADAS) makes provision for easy access and acknowledgment of mycotoxins in different grains, fruits, vegetables and foods in Sub-Saharan Africa. It also enhances robust data collection, management, and analysis, a secure and protected data environment, error reduction and data storage to facilitate regulatory compliance, improved maintainability, standardization, control, predictability, and traceability of data and lower costs due to automation of labor intensive tasks and elimination of redundant work.