In this paper, the Langmuir isotherm, originally derived for the adsorption of three samples of asphaltenes and one sample of resin onto calcite, was modified to fit the adsorption isotherm. The modified Langmuir isotherm parameters obtained from the four linear equations using the different linear method. The aim of this modification is based on the fact that direct application of the Langmuir isotherm often leads to poor data fitting. In the present communication, it is shown that the level of data fitting to the Langmuir isotherm can be improved by a simple modification introducing a concentration dependent factor, X. Four Modified Langmuir linearized isotherm models and one non-linear isotherm model was discussed in this paper, and their coefficients were estimated. In the present study, to study non-linear isotherm model, genetic algorithm was used. A genetic algorithm procedure was utilized to optimize the modified Langmuir constants for a more accurate estimation of the set of model parameters. The obtained results demonstrate that the best fit is obtained using genetic algorithm. Furthermore, it is found that among the mentioned different samples of oil, filtered shale oil follows a multilayer adsorption isotherm.