This report aims at predicting the USA presidential election results based on a set of 18 questions which have only yes or no answers. The historical data (Election Prediction Questionnaire) of victories of presidential party and victories of opposition party along with the answers to following 12 questions were used as the dataset for analysis and research purposes.

1. Has the P-party been in power for more than one term?

2. Did the P-party receive more than 50% of the popular vote in the last election?

3. Was there significant activity of a third party during the election year?

4. Was there serious competition in the P-party primaries?

5. Was the P-party candidate the president at the time of the election?

6. Was there a depression or recession in the election year?

7. Was there a growth in the gross national product of more than 2.1% in the year of the election?

8. Did the P-party president make any substantial political changes during his term?

9. Did significant social tension exist during the term of the P-party?

10. Was the P-party administration guilty of any serious mistakes or scandals?

11. Was the P-party candidate a national hero? 12. Was the O-party candidate a national hero?

The answers were used to train mathematical models such as Decision Tree, KNN, Fisher Discriminant and clustering. This analysis was performed using the Python programming language which has enough libraries for Machine Learning algorithms and is user friendly as well. Ultimately, the questionnaire was filled for Biden election and the prediction results were analysed for useful insights.