But we cannot use simple linear regression in this case because our project data includes several characteristics such as model, year of brand, brand name, transmission, mileage, doors and type, etc. To drive the value of our data, we will therefore focus on using multiple linear regression for this project. We use multiple linear regression defined as a model that “represents the relationship between two or more variables by fitting a linear equation to the observed data. Each value of the independent variable x is associated with a value of the dependent variable y. So this definition directly relates to our methods above for handling data inputs, therefore these statistics according to which our model is adapted to our application. The most important objectives of multiple regression analysis are: i) describe ii) predict iii)