Yang ([1]) proposes the use of a simple estimator of the cumulative distribution function for estimating the functionals with current status data. It is a kernel estimator and is an alternative to the nonparametric maximum likelihood estimator (NPMLE), while the resulting functional estimator has the same asymptotic normal distribution as the NPMLE based estimator. The performance of the kernel based functional estimator very much depends on the choice of bandwidth. In this article, we study the choice of bandwidth for the kernel estimator method of Yang. Through extensive numerical studies, it was found that the bandwidth can be properly chosen using the Jackknife resampling method, and that the kernel based estimator performs well when using a good choice of the bandwidth.