Additive manufacturing techniques have been the focus of studies and technological advances in recent years, obtaining the capability to fabricate pieces with complex geometries easily, rapid and with high precision, allowing the use of different materials, the appearance of new techniques, and a range of applications beyond prototyping. However, Additive Manufacturing techniques are still affected by some deficiencies and challenges such as the absence of sensing and control during the fabrication process that would result in a more reliable process and printed part. This paper shows the development of an inference process using probabilistic graphical models, in order to track the motion of the extrusion nozzle during the printing process using linear encoders