Predicting customer behavior has become a fundamental stone in building the financial

establishments; if a company can predict its client’s next step, good planes can be drawn ac-
cording to the past knowledge. Machine Learning (ML), this powerful tool can be employed

to reinforce the decision-maker planes. In this survey, we focused on running several ML
classifiers since Santander published their dataset online to the kagglers. We had the chance

to run a punch of supervised ML classifiers. The first run using All the dataset using differ-
ent classifiers where the highest accuracy recorded using the Bagging of Naive Bayes (BNB)

classifier with accuracy (92.16%) for the balanced dataset the highest accuracy achieved
through the Naive Bayes (NB) with accuracy (80.12%) and lowest accuracy for both dataset
got through the Decision Tree with accuracy (83.52%) and (58.09%) respectively. Specific
results and discussions can be found through the upcoming sections.