Cramer’s Rule is a helpful way to solve systems of linear equations using determinants, but it has some limits you should know about.

First, Cramer’s Rule works only for square systems. This means the number of equations has to be the same as the number of unknowns. If they don’t match, you can’t use Cramer’s Rule.

Second, this method requires that the determinant of the coefficient matrix isn’t zero. If the determinant, which we can call $D$, is zero, it means there might be no solution or endless solutions. This makes things confusing.

Another big limitation is that it's not very efficient for big problems. For larger systems, finding the determinants can take a lot of time. For example, calculating the determinant of an $n \times n$ matrix usually needs $O(n^3)$ operations. This becomes too slow when $n$ gets large.

Also, Cramer’s Rule can have problems with accuracy. Small errors can build up, making it less reliable than other methods like Gaussian elimination or matrix factorization.

Lastly, Cramer’s Rule doesn’t help us understand the results very well. It doesn’t show if there are connections between the equations or give any geometric views. Other methods can do that.

In short, while Cramer’s Rule is a simple way to solve linear systems, its limits in use, speed, and accuracy make it less useful for more complicated problems.