This article summarizes the recent research related to Low-Level Wind Shear (LLWS), especially on detection and prediction. Wind Shear, especially LLWS, is one of the factors causing aircraft accidents due to weather. LLWS can occur naturally in nature without a cause or caused by various factors. To preventing adverse effects of LLWS, several instruments have been developed to detect the phenomenon. Those are Low-level Wind Shear Alert System (LLWAS), Sound Wave Detection and Ranging (SODAR), Doppler Radar, Terminal Doppler Weather Radar (TDWR), and Light Detection and Ranging (LIDAR). These instruments have various advantages and disadvantages. To consider those advantages and disadvantages, the installation of the equipment at the airport must consider the condition of the runway and the characteristics of the weather on the site. The next step further than detecting is predicting. By predicting the LLWS event, pilots of the aircraft can know the potential location of LLWS and avoid that location. In general, the approach used to predict LLWS is a numerical model and a Machine Learning (ML) model. They have their pros and cons too.