Loosely coupled transformers are commonly used in inductive power transfer (IPT) systems which are inevitable part of electrified transportation. Since efficiency of these systems is mainly dependent on alignment of primary and secondary coils, estimation of coupling coefficient has a significant impact on the performance of IPT chargers. Additionally, coupling coefficient is required to be utilized in real time optimization algorithms, such as impedance matching to improve the stability and transient response of this wireless charger. Furthermore, maintaining a minimum coupling coefficient is a prerequisite for starting charging process in these hands free chargers in order to prevent excessive stresses on electronic components. Estimation of the coupling coefficient can be determined by using a mathematical model of the resonant network. However, resonant network parameters, such as coils’ resistance, core permeability, capacitance, may vary due to aging and temperature fluctuations. These parameters are not tightly controlled or measurable. Moreover, measurement sensor noise also contributes to imprecisions in the calculated coupling coefficient. This manuscript presents a novel approach to accurately estimate the coupling coefficient by employing a parameter estimation approach based on Kalman filter.