LincRNAs enriched with high H3K4me1 and low H3K4me3 signals often have the enhancer-like features which are named as enhancer-associated lincRNAs (elincRNAs). ElincRNAs are considered to be indispensable for target gene transcription, which play important roles in development, signaling events, and even diseases. In this study, we developed a regularized regression model to identify elincRNAs by integrating the genomic, epigenomic, and regulatory data. Application of the proposed method to mouse ESCs reveals that besides the basic well-known epigenetic features H3K4me1 and H3K4me3, more specific epigenetic features, such as high DNA methylation, high H3K122ac, and H3K36me3 were contributed to mark elincRNAs with the best accuracy and precision. Finally, 3729 elincRNAs were identified in mouse ESCs. Furthermore, the elincRNAs and canonical lincRNAs exhibit distinct genomic features, and elincRNAs have the higher CGI enrichment and lower sequence conservation. Through the analysis of transcription regulation, we found that elincRNAs were significantly regulated by NANOG, POU5F1, SOX2 and ESRRB, and were involved in the core transcriptional regulatory circuitry controlling ES cell state Function enrichment analysis further discovered that elincRNAs tended to regulate specific embryonic development biological processes. These results indicated that these two types of lincRNAs had both specific epigenetic and transcriptional regulation mechanism and display distinct functional characters. In conclusion, we presented a credible computational model to prioritize novel elincRNAs, and depicted the atlas of elincRNAs in mouse ESCs, which would help dissect the function roles of lncRNAs during the mammalian development and diseases.