In the modern power system, the power quality issues are prominent. For dealing with power quality issues, harmonic mitigation technologies are inevitable. Hence, design of Harmonic Estimator has become more important aspect because power quality is directly related to customer satisfaction and electricity tariffs. Nature-inspired algorithms have been applied by researchers to develop harmonic estimators. In this paper, harmonic phase and amplitude components are estimated by Artificial Bee Colony (ABC), Teaching- Learning Based Optimization (TLBO), Grey Wolf Optimization (GWO), Sine Cosine Algorithm (SCA), Moth Flame Optimizer (MFO), and Atom Search Optimization (ASO). All the mentioned algorithms are tested on the two standard design problems and comparative analysis of the optimization performance of these algorithms is presented.