In science, computing, and engineering, a black box is a system which can be viewed in terms of its inputs and outputs (or transfer characteristics), without any knowledge of its internal workings. Its implementation is "opaque" (black). The term can be used to refer to many inner workings, such as those of a transistor, an engine, an algorithm, the human brain, or an institution or government.

To analyze an open system with a typical "black box approach", only the behavior of the stimulus/response will be accounted for, to infer the (unknown) box. The usual representation of this "black box system" is a data flow diagram centered in the box.

The opposite of a black box is a system where the inner components or logic are available for inspection, which is most commonly referred to as a white box (sometimes also known as a "clear box" or a "glass box").

A black box is any system whose internal workings are hidden from or ignored by an observer, who instead studies it by examining what goes in (inputs) and what comes out (outputs). The observer looks for patterns in how inputs relate to outputs and uses those patterns to predict the system's behavior, without ever accessing the mechanism inside.

W. Ross Ashby, one of the earliest people to formalize the problem, offered a hypothetical scenario: imagine a sealed device from an alien source. An experimenter can flip its switches, push its buttons, and observe the results: a change in the sound it emits, a rise in temperature, a movement of a dial. By recording many such input–output pairs over time and looking for consistencies, the experimenter builds up a working model of how the device behaves. This model allows prediction ("if I flip this switch, the pitch will change") even though the internal mechanism remains entirely unknown.

The black box approach is useful because many systems—an electronic circuit, a living organism, an economy—are either too complex to analyze component by component or have internals that are physically inaccessible, proprietary, or simply beside the point for the question at hand. Rather than requiring complete knowledge before acting, black box methods let an observer work with what can actually be observed.

The concept is applied in varying ways across fields. In software testing and engineering, black box analysis is typically a methodological choice: the tester treats the system as a black box to verify that specified inputs produce expected outputs, even though the source code could in principle be examined.

In cybernetics and philosophy of science, the concept sometimes carries a stronger implication: that all systems are ultimately black boxes because complete knowledge of internal mechanisms is never fully attainable. Even familiar objects like a bicycle involve forces and processes—interatomic bonds, material properties—that thwart direct inspection. Most practical uses fall somewhere between these poles: a researcher may begin with black box methods because internals are currently inaccessible, then gradually "open" the box as new tools or techniques permit, while recognizing that some opacity will always remain.