Three-dimensional (3-D) structural models of RNA are essential for understanding of the cellular roles played by RNA. Such models have been obtained by a technique based on a constraint satisfaction algorithm that allows for the facile incorporation of secondary and other structural information. The program generates 3-D structures of RNA with atomic-level resolution that can be refined by numerical techniques such as energy minimization. The precision of this technique was evaluated by comparing predicted transfer RNA loop and RNA pseudoknot structures with known or consensus structures. The root-mean-square deviation (2.0 to 3.0 angstroms before minimization) between predicted and control structures reveal this system to be an effective method in modeling RNA.