Overfitting is a common problem in the development of predictive models. It leads to an optimistic estimation of apparent model performance. Internal validation using bootstrapping techniques allows one to quantify the optimism of a predictive model and provide a more realistic estimate of its performance measures. Our objective is to build an easy-to-use command, bsvalidation, aimed to perform a bootstrap internal validation of a logistic regression model.