Emotion regulation is a key developmental skillset, but many existing measures rely on self-report or laboratory-based measurement approaches. This study aimed to develop a training and implementation protocol for the widely used Facial Expression Coding System (FACES) to be used in real-world settings with pre-recorded video data. A revised coding system with supplemental guidelines and training procedures was developed to use FACES with video data recorded in special education classrooms. This system resulted in adequate interrater reliability as well as reduced training time for coders. Specific training methods included close study of code definitions, coding of practice video, quantitative analysis of observation data to generate interrater agreement and kappa statistics, review of comparison charts to identify discrepancies between coder and training observations using the Noldus Observer XT software, and post-observation discussions. The revised FACES protocol and new training method presented here offer a more robust, efficient, and versatile tool that can be applied to systematic behavior observations conducted of students in real-world classroom settings.