For dichotomous dependent variables, you could use logistic regression.

However, I would discourage you from dichotomizing your independent variables (leave them in their original metric). Dichotomizing leads to a loss of information and can reduce statistical power. There is almost never a need to dichotomize variables from a statistical perspective because there are many statistical procedures available that can handle ordinal-polytomous and/or continuous (metrical, interval-scale) variables. When you type "dichotomizing continuous variables" into Google Scholar, you will find a large number of relevant references that explain why this is a bad idea.

Hello, considering that the criterion variable is dichotomous, I suggest using logistic regression to make predictions. Predictor variables can be dichotomous, or continuous. I recommend referring to Tabachnik Fidel's book (2019) for more information.