Microbiologically influenced corrosion (MIC) is a prevalent and serious form of metal corrosion that can cause substantial economic loss. Due to the complexity of the MIC process, developing techniques for detecting and controlling MIC is a key challenge in industrial corrosion science. This paper systematically reviews the research progress of MIC detection methods and prediction models. The detection methods of MIC include electrochemical techniques, bioanalytical methods, radiation detection, microscopy, and biosensing approaches. Each detection technique has its own merits and limitations, and the cooperative application of multiple techniques is needed to comprehensively evaluate the MIC process. The prediction models of MIC can be categorized into those based on risk assessment-based, mass transfer-based, and comprehensive electrochemistry-based models. Given the complexity of MIC systems, no single model has yet been capable of fully predicting MIC phenomena. It is recommended that future efforts be directed toward developing integrated models that account for influential factors and mechanisms, resolving measurements of the microenvironment within biofilms, in order to enhance the accuracy of MIC prediction.