iLEC-DNA is an artificial intelligence (AI) based tool that makes use of sequence-derived physicochemical and gap-based nucleotide distribution features and a support vector machine classifier (SVM) to accurately predict long extrachromosomal circular DNA across three different species i.e., Homo sapiens(HM), Arabidopsis thaliana (AT), and Saccharomyces cerevisiae(SC/YS) only using raw DNA sequences. iLEC-DNA produces significant performance across the majority of benchmark iLEC-DNA datasets in k-fold cross-validation and independent test sets based on the evaluation. iLEC-DNA web interface enables the user to perform multi-dimensional analysis of DNA sequences, training and optimizing the machine learning model from scratch, using pre-trained models of different species to make inferences on new sequences, and downloading interactive artifacts during the lifetime of the session.