User-specific subspace method, such as CLAFIC concatenates the speech matrices side by side leads to a high dimensional feature space before forming the correlation matrix. We propose an enhanced CLAFIC method in speaker verification, coined as Probabilistic 2D CLAFIC which apply a straightforward 2D speech matrix projection technique for feature dimension reduction and GMM is used to construct the speaker model to boost up the performance. Our results show the superior performance and low computation time in the proposed system.