Real-time recognition of formation lithology is critical for promptly adjusting drilling parameters， effectively controlling wellbore trajectory， and identifying subsurface reservoirs. Compared to traditional methods of identifying lithology， real-time recognition through monitoring parameters while drilling offers advantages such as convenience， efficiency， real-time accuracy， environmental compatibility， and energy efficiency. In this paper， around the lithology identification technology based on real-time parameters while drilling， the parameters according to different applications such as coal exploration and oil and gas reservoir exploitation are classified. Through the analysis of the current research status of drilling measurement and control technology and equipment， the technology for collecting and transmitting real-time parameters while drilling is introduced. Additionally， the characteristics and applications of machine learning algorithms， multivariate statistical analysis， grey relational analysis， and cross-plotting methods are also discussed. Through application cases， it compares and analyzes four types of lithology identification methods based on real-time parameters while drilling. Ultimately， the key technical issues in real-time lithology identification research is summarized， the deficiencies and challenges in development and engineering applications are analyzed， and the recommendations are provided.