In vitro selection is a versatile experimental technology for screening large random-sequence libraries of nucleic acid molecules for a specific function, such as binding or catalysis. It has enabled discovery of numerous nucleic acid molecules binding diverse targets (e.g., organic molecules, antibiotics, proteins), and novel ribozymes. Such synthetic RNAs are being used to develop RNA-based biosensors, inhibitors of protein function, and tools for exploring biological interactions. However, the probability of finding complex RNA molecules in random pools is low because simple motifs dominate such pools. To overcome this problem, we have developed methods for designing structured pools using concepts such as modeling and optimization of RNA pool synthesis, analysis of RNA structure space using molecular graphs, and screening of large sequence pools for active RNA species. These methods parallel advances in combinatorial chemistry for design, analysis and synthesis of compound libraries used in drug discovery. Specifically, we design structured RNA pools by optimizing the sequence/structure space to yield the target or user-defined structural characteristics. The target structured pool corresponds to an optimal combination of nucleotide transition matrices used for pool synthesis, starting sequences, and associated pool fractions. Our pool design method has been automated and made available through the webserver RAGPOOLS that offers a theoretical companion tool for RNA in vitro selection. Thus, our designed structured RNA pools can serve as a guide to researchers who aim to analyze and synthesize RNA pools with favorable properties for current biomolecular engineering applications.