The 2D facial landmark alignment method, implemented in C++ in the open source libraries DLIB and Deformable Shape Tracking (DEST), is used in several applications such as driver drowsiness detection. The most challenging of these applications require fast video frame processing. Therefore, the alignment of the facial landmarks in a single video frame has to be performed with the minimum possible latency without precision loss. In this paper, the DEST implementation of the face alignment method that is based on regression trees is heavily restructured to reduce latency. The resulting face alignment predictor is implemented in C. The elimination of multiple nested routine calls, excessive argument copying, type conversions and integrity checks lead to a software implementation that is 240 times faster than the one provided in the DEST library. Moreover, the structure of the new face alignment predictor is appropriate for hardware implementation on a Field Programmable Gate Array (FPGA) for further acceleration1.