The skin is a prime and most visible organ of the body. Skin act as a barrier against injury and bacteria. There are six different categories of skin diseases which shares somewhat same features. In this group psoriasis is a major skin disease. This paper focuses the major clinical and histopathological attributes influences on psoriasis disease of human body. Disease diagnosis is one of the applications of data mining. Prediction used to predict the relationship by using regression equation. This paper originates the relationship among input and response attributes for improving disease diagnosis in medical area. The Response Surface Methodology (RSM) is make used for develops a relationship between input attributes of skin disease and predicts the psoriasis patients with the help of independent and dependent variables. The performance of RSM model shows the developed empirical relationship and it has the greatest conformity with test results. The Analysis of Variance (ANOVA) is performed to mathematical analysis of the outcome. In summary, the developed empirical model is suitable for skin disease prediction.