I'm trying to make a model which can predict test scores. I'm currently using a simple linear regression model but receiving an accuracy score of close to 0 due to the fact that it's guessing a single number as the score. I was wondering if there was a way to have the model predict a range of about 10 numbers and if the true number is in that range it is marked as a correct guess.
It seems like you are using a LogisticRegression, LogisticRegression is in fact not for regression, it is for classification (for example, is the input data class a or b).
use sklearn.linear_model.LinearRegression for linear regression, read this for more details
There are also many other regression algorithms that I cannot list all in an answer. If you want to use regressions other than simple naive linear regression, read this for all available supervised learning algorithms scikit-learn provides, Ridge regression and SVR might be good places to start with.