Deception detection through facial and audio transcript features has gained traction due to its potential in enhancing security and communication integrity. This review aims to consolidate existing research on leveraging facial and audio features for identifying deceptive behavior. The motivation behind this study is the increasing demand for reliable deception detection mechanisms in various domains, including security and psychology. Despite advancements, limitations persist in achieving high accuracy across diverse contexts and individual differences. The objective of this review is to evaluate the effectiveness of different methods used in detecting deception from facial expressions and audio cues, identifying strengths and weaknesses of each approach, and suggesting future directions for improving accuracy through advanced techniques.