NP完全或NP完备（NP-Complete，缩写为NP-C或NPC），是计算复杂度理论中，决定性问题的等级之一。NPC问题，是NP（非决定性多项式时间）中最难的决定性问题。因此NP完备问题应该是最不可能被化简为P（多项式时间可决定）的决定性问题的集合。许多人推测若任何NPC问题得到多项式时间的解法，那此解法就可应用在所有NP问题上。更详细的定义容下叙述。

一个NPC问题的例子是子集合加总问题，题目为

这个问题的答案非常容易验证，但目前没有任何一个够快的方法可以在合理的时间内（意即多项式时间）找到答案。只能一个个将它的子集取出来一一测试，它的时间复杂度是Ο(2)，n是此集合的元素数量。

In computational complexity theory, a decision problem is NP-complete when it is both in NP and NP-hard. The set of NP-complete problems is often denoted by NP-C or NPC. The abbreviation NP refers to "nondeterministic polynomial time".

Although any given solution to an NP-complete problem can be verified quickly (in polynomial time), there is no known efficient way to locate a solution in the first place; indeed, the most notable characteristic of NP-complete problems is that no fast solution to them is known. That is, the time required to solve the problem using any currently known algorithm increases very quickly as the size of the problem grows. As a consequence, determining whether or not it is possible to solve these problems quickly, called the P versus NP problem, is one of the principal unsolved problems in computer science today.