The gasoline blending is a critical aspect in oil refinery operations. There are multiple blending rules in prior art to predict the chemical or physical property of the blend. But none of the prior method focuses on obtaining the best blending rule for each feature used in creating the soft-sensor. A method and system for generating a soft-sensor for getting desired property of a blend by optimizing a set of blending rules for each feature used for creating soft-sensor have been provided using data from individual components of the blend. The method comprises automated soft-sensor creation using multiple data sources. Further, the method involves finding best blending rule for each feature used for building the soft-sensor or the blending model to predict property of the blend. The soft-sensor developed using data of components used for blending is adapted to predict mixture or blend property with limited tuning.