Due to problems followed by asphaltene deposition, which cause many remedial processes and costs, it seemed necessary to develop equations for determining asphaltene precipitation quantitatively or qualitatively. In this study a new scaling equation as a function of temperature, molecular weight, and dilution ratio (solvent) has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of different precipitants (solvents). The proposed methodology utilizes least square support vector machines/regression (LSSVM/LSSVR) to perform nonlinear modeling. This paper proposes a new feature selection mechanism based on coupled simulated annealing (CSA) optimization in an attempt to tune the optimal parameters. CSA-LSSVM has the good capability of characterizing the nonlinear behavior. The performance of the proposed LSSVM algorithm is highly satisfactory and demonstrated by residuals and statistical indicator and was compared with previous works. The results showed its superiority to previous and highly dependent performance. (C) 2012 Elsevier B.V. All rights reserved.