Aim: Efficient novel fashion Prediction using MNIST dataset by image classification using a support vector machine and Logistic Regression. Materials and Methods: This study contains 2 groups i.e Support Vector Machine and Logistic Regression. Each group consists of a sample size of 10 using G-power setting parameters: (α=0.05 and power=0.86) power value 0.4 respectively Results: The Support Vector machine (SVM) is 91.2% which is more accurate than Logistic Regression (LR) of 72.6% in Fashion Forecasting and attained the significant value 0.094 Conclusion: The Support vector machine model is significantly better than the Logistic Regression in novel fashion Forecasting.