Predicting time series data
Best approach would be to perform data preparation first:

Remove features (columns) with no variance in it (you could use: sklearn feature_selection)
one-hot-encoding of categorical features
insert a lag column of -t steps

If you have more than one explanatory variable, the process is called multiple linear regression. Instead of using a regression model you could also use other learners like XGBoost or LSTMs