Let's take a simple voltage divider AND you are only interested in resistor tolerances, not supply tolerances (assume psu is ideal) [![enter image description here][1]][1] It is trivial to calculate the nominal, minimum and maximum max: \$10\cdot \frac{10k*1.01}{(10k*1.01) + (10k*0.99)}\$ = 5.05V nom: \$10\cdot \frac{10k}{10k + 10k}\$ = 5V min:\$10\cdot \frac{10k*0.99}{(10k*1.01) + (10k*0.99)}\$ = 4.95V Can a Monte-Carlo output this value? Probably, a very very VERY small probably occurrence. Why? A Monte-Carlo simulation will generate a **random** value within stated bounds (normal distributed, 1%, mean value). Statistically speaking it could generate, but this is a ***one in a billion*** type occurrence. To then pick the absolute max and hte absolute minimum, in the same run? I would rather bet on a national lottery. [![enter image description here][2]][2] The absolute max/min output "worst of the worst" is a best suited for pen & paper, excel, mathCAD, Jupyter etc ... and is extremely valuable in determining whether a design will operate over all possible tolerances (very useful for stress calculations). Real world type behaviour? the probabilistic approach relies on these types of sweeps. In practice both are useful as you can take credit since 6\$\sigma\$ covers 99.999997% and thus anything outside of this is 3.4 errors per million So in short.. Will a Monte-Carlo run provide the extreme outputs? probably. If you want to know the extreme outputs then most tool can be set for extreme value calculation, but you need to guide them to determine which combination will provide the maximum/minimum [1]: https://i.sstatic.net/hbM3F.png [2]: https://i.sstatic.net/5coik.png