Soft Computing Model always composed of Fuzzy logic, Neural Network, Genetic algorithm etc. Most of the time, these three components are combine in different ways to form model. Fuzzy- Neuro Model, Neuro- GA model, Fuzzy- Neuro- GA model etc. All this combination is widely used in prediction of time series data. If in a time series data, initial change are observed during some time interval, the final value of this data must be predicted. In this paper, an effort has been made to use soft computing approaches for predicting a final product of a time series data. The data is taken from a statistical survey has been conducted by a group of certain agricultural personnel on different mustard plant under the supervision of Prof. Dilip dey, Bidhan Chandra Krishi Viswavidayalay West Bengal, India. In this paper, the models of soft computing using neural network based on fuzzy input and genetic algorithm have been tested on same data and based on error analysis (calculation of average error) a suitable model is predicted for this data.