This chapter presents a novel method for the pitch recognition of the musical consonance (i.e., unison or octave) using genetic algorithm (GA). GA is a kind of optimization techniques based on natural selection and genetics. In our method, the pitch recognition is performed by the following two-step procedure: (i) search space reduction using comb filter estimation, and (ii) evolutionary parameter estimation of tone parameters such as notes and volumes by minimizing error between a target waveform and a synthesized waveform using sound templates with estimated parameters. The potential capability of the system is demonstrated through the pitch estimation of randomly-generated consonances. Experimental results show that the system can successfully estimate chords with more than 84% success rate for two-note consonances, and more than 71% success rate for three-note consonances.