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The rapid development of modern computational technology has created an entirely new environment for the efficient use of the theoretical construction in many areas of applied research. The theoretical approach has proven to be especially beneficial in chemistry and allied sciences, where the experimental-analysis and artificial development of new compounds and materials can be time-consuming, laborious, expensive or even hazardous. Hence there is a need of alternate approach to experimental process (M. Karelson et al., 1999). A feasible estimation method should satisfy the following conditions: (i) It can be applicable to diverse set of compounds; (ii) It requires minimum number of inputs; (iii) It should provide reasonable accuracy to the predicted output; (iv)It needs minimum computation time (Yaffe et al., 2001). Numerous estimation methods are reported in literature to predict a given physical or chemical property. On the other hand, as the heterogeneity in the chemical structure of the compounds increases, property prediction becomes less reliable and consumes more time. The different approaches generally used for prediction of physical properties can be classified into the following categories(1) Correlation based on experimental data; (2) Group contribution method based on fragments; (3) Correspondence theorem based on critical properties. The first approach requires experimental data as input (such as density boiling point etc.) are limited to compounds for which such experimental data available. Second approach requires fragments such as number of bonds, functional groups etc for correlation. In the third approach, due to the lack of availability of critical properties, prediction errors are considerably high and hence its application is limited. This method has no reliability with multiple functional groups for isomers. Therefore there is a necessity of reliable property prediction models capable of a prior prediction of properties of diverse set of compounds, thereby reducing the burden of experimental process (Yaffe et al., 2001).