Nowadays the manufacturing is facing the critical challenges from various aspects including the trend of moving towards the new era of Industrial 4.0 [1]-an analytical and predictive driven production thinking, the Smart Factory. To effectively embed the necessary processes for analytics, a new way of modeling the process flows is essential to realize the goal of the predictive lean production. To reach these objectives, this paper presents a novel process modeling approach for analytics which is vital to the practitioners and the industries. The analysis of the smart factory theme includes the statistics, the data mining, and the operation research approaches [2] based on the various management improvements or the prediction objectives. The proposed process modeling for analytics extends the XML (eXtensible Markup Language), which is also commonly used in software engineering [3]. The purpose of using this is to streamline the latter integration with the analytical processes among the software systems and will play a key part of the factory knowledge management for continuous optimization.