Paddy drying is one of the main operations on the rice milling industry and it has a wide impact in terms of kernel quality, infestation reduction and costs of operation. That is why process control is one of the main fields to ensure a successful operation. This paper presents the development of an industrial scale drying rate prediction model. The model includes on his structure mass balance equations, drying rate and bulk density equation and an experimental expression that estimates the rate of change in moisture as a function of the dry basis kernel water fraction, Sherwood number, mass transfer Biot number and a proposed non-dimensional temperature -Nt-. The importance of including -Nt- parameter is based on the thermal gradients between the drying air, internal kernel water and the installation environmental conditions. These factors create a distinctive characteristic from other drying rate prediction models because they associate the process with environmental conditions of the location where drying operation takes place.