Ribosomal ribonucleic acid (rRNA) is essential for the proteins synthesis, one of the most basic biological processes. To understand its mechanisms, the knowledge of the rRNA structure is required as it forms the structural core of the protein synthesizing unit, the ribosome. Experimental identification of rRNA structure is extremely technically difficult. Secondary structure, a simplified structural model, can be predicted, but prediction for rRNAs is hindered by extreme length of rRNA sequences. Thus, only few eukaryotic rRNA structures are available so far. We will employ information about evolutionary conserved segments of eukaryotic rRNA sequences for secondary structure prediction. An algorithmic workflow integrating the secondary structure prediction pipeline, visualization algorithm and database of the predicted structures will be developed. The predicted rRNA structures will be used for a novel bioinformatic identification of evolutionary conserved structural motifs in eukaryotic rRNAs that may bring new insights into the role of rRNA in the protein synthesis.