A first step would be counting the nested loops and looking at the number of times they execute. If you have three nested loops, each running from 1 to x, and inside the three you have operations taking constant time (i.e. not dependent on the size of any variable) then the complexity is [itex]\mathcal{O}(n^3)[/itex].
If you're using bignums or the like you'll have to look into how much each operation costs based on the size of the numbers -- that's usually log(x)^k log(log(x))^n for some k and n. If you have a loop from 1 to x doing schoolbook multiplication on a bignum of size x, that's complexity [itex]\mathcal{O}(x(\log x)^2)[/itex].
If you're using standard library functions, most programming language standards will specify the mandatory asymptotic running time in the standard. If you're wanting to analyse your own code, then a good book (the standard in universities, pretty much), is Introduction to Algorithms by CLRS.