In this paper, the nonparametric kernel method is used to estimate the well known overlapping coefficient known as Matusita 𝜌. Due to the complexity of finding the formula expression of this coefficient when using the kernel estimators, we suggest to use the numerical integration method to approximate its integral as a first step. Then the kernel estimators were combined with the new approximation to formulate the proposed estimators. Two numerical integration rules known as trapezoidal and Simpson rules were used to approximate the interesting integral. The proposed technique produced two new estimators for 𝜌. The proposed estimators are studied and compared with existing estimator developed by Eidous and Al-Talafheh (2020) via Monte-Carlo simulation technique. The simulation results clearly demonstrated the usefulness and efficiency of the new technique for estimating 𝜌.