In this work, the group contribution approach has been used in combination with the linear isotherm regularity (LIR) equation of state to estimate pvT properties of primary, secondary and tertiary alcohols, ketones and 1-carboxylic acid. We assume each of these organic compounds as a hypothetical mixture of methyl , methylene and a functional group, in which the interaction potential of each pair is assumed to be the average effective pair potential. Then, the LIR equation of state (EOS) has been extended to such a hypothetical mixture. Three basic compounds, namely propane, n -butane and cyclohexane, are used to obtain the contribution of methyl and methylene groups in the EOS parameters and also other appropriate compounds are used to obtain the contribution of the functional groups, such as: 1-pentanol for the contribution of ?CH 2 OH, 2-pentanol for the contribution of CHOH, 2-methyl-2-propanol for the contribution of COH, 2-pentanon for the contribution of C=O and 1-pentanoic acid for the contribution of ?COOH groups. The calculated EOS parameters along with the modified EOS are then used to calculate the density of different compounds at different pressures and temperatures with the average percentage error less than 1.2. Also, the isothermal compressibility ( ? T ), thermal pressure coefficient ( ? ) and the thermal expansion coefficient ( ? p ) are calculated for some hydrocarbons with absolute percent deviation less than 1.0. Then, a new method based on the modified Enskog theory (MET) is presented for calculation of traort properties at high densities ( ? ? c ). To make the approach more general, we have used principle of corresponding states to give viscosity expression independent of fluid in terms of reduced variables. In next section, a wavelet neural network (WNN) has been used to predict density of 35 organic fluids such as n -alkanes, cycloalkanes, primary, secondary and tertiary alcohols, ketones and 1-carboxylic acids for witch the number of carbon atoms varying from 2 to 10, over a wide range of temperature and pressure. The WNN model has been constructed using 11 descriptors consisting of temperature, pressure, the number of carbon atoms of each compound and 8 descriptor based on group contribution method (GCM) namely, the number of methyl, terminal methylene (methylene groups each attached to one methyle group), middle methylene (methylene groups at the middle of chain which each of them attached to two methyle groups), -CH 2 OH, ?CHOH, COH, ?C=O and -COOH groups. The average absolute error for density prediction was found to be lower than 0.31. This approach was successfully applied to the isothermal compressibility ( ? T ), thermal pressure coefficient ( ? ), the thermal expansion coefficient ( ? p ) and viscosity ( ? ).