Long non-coding RNAs (lncRNAs) comprise the most representative transcriptional units of the mammalian genome, and they’re associated with organ development that can be associated with the emergence of diseases, such as cardiovascular diseases. Thus, we used bioinformatic approaches, machine learning algorithms and statistical techniques to define lncRNAs involved in mammalian cardiac development. We used a single-cell transcriptome dataset generated from 4 embryonic and 4 postnatal stages. Our study identified 8 distinct cell types, novel marker transcripts (coding/lncRNAs) and also, differential expression and functional enrichment analysis reveal cardiomyocyte subpopulations associated with cardiac function; meanwhile modular co-expression analysis reveals cell-specific functional insights for lncRNAs during myocardial development, including a potential association with key genes related to disease and the “fetal gene program”. Our results evidence the role of particular lncRNAs in heart development, and highlights the usage of co-expression modular approaches in the cell-type functional definition.