Logit and Probit Models Are More Appropriate Than Linear Probability

Logit and probit models are more appropriate than linear probability models because:

A) Logit and probit can estimate probabilities that are negative
B) Logit and probit cannot estimate probabilities that are greater than one
C) Logit and probit cannot estimate probabilities that are negative but not greater than one
D) Logit and probit cannot estimate probabilities that are negative or greater than one