The Tr(R2) control chart can be utilized to monitor multivariate variability processes. Nevertheless, it is currently uncertain how exactly Tr(R2) is distributed. In order to resolve this matter, this article proposes a Tr(R2) control chart based on the bootstrap method to monitor process variability. The control limits of the Tr(R2) control chart are set based on the percentiles of the Tr(R2) statistics obtained from bootstrap samples. Through simulation studies, the values of ARL0 and ARL1 are determined in order to assess the performance of the suggested control chart. The outcomes of the simulation demonstrate that the proposed control chart can produce accurate ARL0 values under conditions of \(\alpha = 0.0027, \;0.005, \;0.01,\) and 0.05. In addition, the proposed control chart also demonstrates very good performance in detecting shifts in variability when monitoring multivariate processes.