In this article, a facial expression recognition technique has been proposed. In this method, initially, a face image is segmented into different sub-images like left eye, right eye, mouth, nose, etc. Then, two-dimensional principal component analysis (2DPCA)-based transformation is performed on each sub-image separately to extract the features. Lastly, classification operation is made to categorize the expression of faces. To demonstrate the effectiveness of the proposed method, results are compared with other existing PCA-and 2DPCA-based methods in terms of overall classification accuracy. Results for the proposed method are found to be encouraging.