在计算复杂度理论中，一个复杂度类指的是一群复杂度类似的问题的集合。一个典型的复杂度类的定义有以下型式：

例如NP类就是一群可以被一非确定型图灵机以多项式时间解决的决定型问题。而P类则是一群可以被确定型图灵机以多项式时间解决的决定型问题。某些复杂度类是一群函式问题（Function problem）的集合，例如FP。

许多复杂度类可被描述它的数学逻辑（mathematical logic）特征化，请见可描述的复杂度（descriptive complexity）。

而Blum公理用于不需实际计算模型就可定义复杂度类的情况。

In computational complexity theory, a complexity class is a set of problems of related resource-based complexity. A typical complexity class has a definition of the form:

Complexity classes are concerned with the rate of growth of the requirement in resources as the input n increases. It is an abstract measurement, and does not give time or space in requirements in terms of seconds or bytes, which would require knowledge of implementation specifics. The function inside the O(...) expression could be a constant, for algorithms which are unaffected by the size of n, or an expression involving a logarithm, an expression involving a power of n, i.e a polynomial expression, and many others. The O is read as "order of..". For the purposes of computational complexity theory, some of the details of the function can be ignored, for instance many possible polynomials can be grouped together as a class.