It has been found that some RNA functions are determined by the actual folding kinetics and and not always by the RNA's nucleotide sequence or its native structure. In this presentation, we describe some new computational tools for simulating and analyzing RNA folding kinetic metrics such as population kinetics, folding rates, and the folding of particular sub-sequences. These methods first build an approximate map (or model) of the folding energy landscape from which the population kinetics are analyzed by solving the Master Equation on the map. We compare these approximated methods with other computational methods that begin with a comprehensive free energy landscape, illustrating that the smaller, approximate map captures the major features of the complete energy landscape. As a result the presented methods scale to larger RNAs (e.g., RNAs of more than 200 nucleotides) and run much faster.