Question on Regression

To begin with, you need to provide us more information regarding what kind of data you have, what your objectives and research questions were so we can provide you with relevant help so as not to speculate. However, a general principle which I have used many often successfully is to conduct univariate regression on the combined effect of each categorical variable and then used follow on with multiple regression. If the combined effect of that categorical variable is not significant, there is no need to declare the classes for such such variables in the multiple regression model or if some of the classes are similar in nature, you could collapse then into one class and then test their combined effect again by repeating the process above. You will do this for all the categorical variables in your data set. Yes, you can use linear regression to achieve this but having 100 classes for one categorical variable, I am afraid that you will be dealing with so many degrees of freedom which might have some serious effects on the optimality of your fitted model and its predictive power so I will suggest you collapse the classes to fewer if that is possible, bearing in mind your research questions and objectives.