The aim of this research is to discover the continuance and recommendation intention of higher education students who are using ChatGPT. Specifically, we proposed an extend technology continuance theory (TCT) by integrating the recommendation intention. A structured Google form is used to collect the data from the higher education students especially engineering college students in India. A sum of 307 responses gathered and employed for the purpose of data analysis. Structured equation model (SEM) was used to test the research hypothesis. The study found that perceived usefulness, attitude, and satisfaction were significant predictors of continuance intention, while satisfaction and continuance intention themselves predicted recommendation intention, indicating that students who perceive ChatGPT as useful, have a positive attitude towards it, and are satisfied with it are more likely to continue using it and recommend it to others. These results underscore the importance of user satisfaction and positive attitudes in fostering continued engagement and advocacy for AI-driven chat systems. The study's findings were evaluated in terms of their discussion, limitations and implications for future research.