Clusterwise linear regression aims at partitioning a dataset into clusters characterized by their own regression coefficients. To deal with multiblock data, an extension of clusterwise regression to multiblock PLS is proposed. As this method is component-based, it may handle high dimensional data. The interest of the proposed method will be illustrated on the basis of a simulation study