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This papers reports on methodologies and outcome of a study aiming at developing robust tool to evaluate and classify histology images of cervical cancer. Using the histology images acquired from the pathology laboratories in an Indonesian hospital, this study aims to classify cervical biopsy images based on four well known discriminatory features a) the ratio of nuclei to cytoplasm b) diameter of nuclei c) shape factor and d) roundness of nuclei. In this study, the cervical histology images are classified into three categories: 1) normal, 2) pre cancer and 3) malignant. The final system will take as input a biopsy image of the image of the cervix containing the epithelium layer and provide the classification using the new automated approach, to assist the pathologist in cervical cancer diagnosis.