A bootstrap resampling scheme is applied to a nonparametric estimator of the change-point in a sequence of independent observations. The nonparametric estimator is based on the Kolmogorov-Smirnov norm as proposed by Carlstein (1988). The consistency of the bootstrapped estimator along with the rate of convergence are provided. In addition, an exponential bound for the error probability is shown to hold for all most all given realizations.