LTR_FINDER is an efficient web server designed for the prediction of full-length LTR retrotransposons in large-scale DNA sequences. It addresses the challenge of identifying these elements, which play crucial roles in gene and genome evolution. The tool considers common structural features such as Long Terminal Repeats (LTRs), Target Site Repeats (TSRs), Primer Binding Sites (PBSs), Polypurine Tracts (PPTs), and enzyme domains like Reverse Transcriptase (RT), Integrase (IN), and RNaseH (RH). LTR_FINDER uses rapid algorithms to construct reliable LTRs and predict accurate element boundaries through a multi-refinement process. It offers two output types: full-output and summary-output, both of which include detailed predictions and visual diagrams. The server is freely accessible and has been tested on the Saccharomyces cerevisiae genome, demonstrating high sensitivity and specificity. Future improvements include enhanced user interface, specialized reporting for LTR elements near functional units, and the ability to detect nested LTR elements.LTR_FINDER is an efficient web server designed for the prediction of full-length LTR retrotransposons in large-scale DNA sequences. It addresses the challenge of identifying these elements, which play crucial roles in gene and genome evolution. The tool considers common structural features such as Long Terminal Repeats (LTRs), Target Site Repeats (TSRs), Primer Binding Sites (PBSs), Polypurine Tracts (PPTs), and enzyme domains like Reverse Transcriptase (RT), Integrase (IN), and RNaseH (RH). LTR_FINDER uses rapid algorithms to construct reliable LTRs and predict accurate element boundaries through a multi-refinement process. It offers two output types: full-output and summary-output, both of which include detailed predictions and visual diagrams. The server is freely accessible and has been tested on the Saccharomyces cerevisiae genome, demonstrating high sensitivity and specificity. Future improvements include enhanced user interface, specialized reporting for LTR elements near functional units, and the ability to detect nested LTR elements.