The Magnetic Flux Leakage (MFL) system has become the key solution to the need for effective pipeline predictive control and maintenance, as it provides non-destructive tests. MFL systems work by introducing a magnetic field into the pipeline material and measuring changes in that field due to features such as corrosion, cracks, and metal loss. These variations which are detected by sensors give real time information on the condition of the pipeline. This review algorithm focuses on use of MFL as a predictive control technique, with an emphasis on the capacity to predict failure and improve safety. MFL combined with state-of-the-art data analytic and machine learning enhances the ability to detect defects and promote timely maintenance for efficient pipeline operations across various industries. This review analysed 81 existing studies which are taken from the year 2019 to 2024. Elaborate discussions on Predictive Control Strategies for Pipeline Management, Magnetic Flux Leakage (MFL) Technique in Modern Pipeline Maintenance, the Evolution and Impact of MFL in Pipeline Inspection, Pipeline Defects: Detection and Classification Using MFL, integrating MFL Systems into Predictive Maintenance Frameworks, recent Advancements in Magnetic Flux Leakage Sensor Technology. Furthermore, tables have been provided which explains the limitations of the techniques are discussed.