信息论（英语：information theory）是应用数学、电机工程学和计算机科学的一个分支，涉及信息的量化。信息论是由克劳德·香农发展，用来找出信号处理操作的基本限制，如数据压缩、可靠的存储和数据传输的。自创立以来，它已拓展应用到许多其他领域，包括统计推断、自然语言处理、密码学、神经生物学、进化论和分子编码的功能、生态学的模式选择、热物理、量子计算、语言学、剽窃检测、模式识别、异常检测和其他形式的数据分析。

熵是信息的一个关键度量，通常用一条消息中需要存储或传输一个符号的平均比特数来表示。熵衡量了预测随机变量的值时涉及到的不确定度的量。例如，指定掷硬币的结果（两个等可能的结果）比指定掷骰子的结果（六个等可能的结果）所提供的信息量更少（熵更少）。

Information theory is a branch of applied mathematics, electrical engineering, and computer science involving the quantification, storage, and communication of information. Information theory was originally developed by Claude E. Shannon to find fundamental limits on signal processing and communication operations such as data compression. Since its inception in a landmark 1948 paper by Shannon entitled "A Mathematical Theory of Communication", it has been broadened to find applications in many other areas, including statistical inference, natural language processing, cryptography, neurobiology, the evolution and function of molecular codes, model selection in ecology, thermal physics, quantum computing, linguistics, plagiarism detection, pattern recognition, anomaly detection and other forms of data analysis.