Precision feeding is a promising way to improve feed efficiency and thus economic and environmental sustainability of livestock production. A decision support system (DSS) was built to determine in real-time the nutritional requirements of animals and feed characteristics (i.e. composition, amount) for an application of precision feeding in pig and poultry commercial farms. This tool, dedicated to animals managed individually or in groups, is designed with a modular structure for adaptation to different feeder devices, species and production stages. The modules are built to perform specialized tasks in a cooperative way. It includes a data management module with a proper characterization of data by meta-data definition for precision feeding. It ensures standard encoding to allow data interoperability from any platform. Other modules are dedicated to data verificatrion and correction for inclusion in a database, prediction of most probable body weight (BW) gain and feed intake (ad libitum or restricting feeding), and the calculation of nutritional requirements. The BW and feed intake prediction is based on dynamic data analyses. For that, specific methods have been evaluated and selected depending on the number of available data, data type (BW or feed intake), and recording frequency. The calculation of nutritional requirements is performed using nutritional models specific for a species or production stage. These two modules are currently designed for healthy animals and will be refined to extend prediction to a larger range of field situations (e.g. health problems, climatic conditions) with nutritional models in development/refinement in other workpackages of the project. The general specifications of this DSS and dynamic data analyses will be illustrated for growing pigs. This study is part of the Feed-a-Gene project and received funding from the European Union’s H2020 program under grant agreement no. 633531.