There is something called variance inflation factor (VIF), If VIF value is greater than ten (VIF > 10) then there is a collinearity problem. This Video explains how to assist the problem in a formal way.
Also, Find the prediction model equation in this video tutorial and explanation of model and assumptions
In statistics, multicollinearity (and also collinearity) is actually an occurrence in which two or more predictor variables in a multiple regression model are highly correlated, meaning that one can possibly be linearly predicted from the others with a significant degree of accuracy.
Collinearity happens when 2 predictor variables (e.g., x1 and x2) have a non-zero correlation in a multiple regression. Multicollinearity happens when more than 2 predictor variables (e.g., x1, x2 and x3) are inter-correlated.