Bangladesh is one of the most vulnerable countries of the world in the event of climate change due to its unique geographical location. This study assessed the impact of climate change on precipitation and temperature extremes over Bangladesh from Coupled Model Intercomparison Project Phase 6 (CMIP6) models under four SSP-RCP (Shared Socioeconomic Pathway-Representative Concentration Pathway) scenarios (SSP126, SSP245, SSP370, and SSP585). At first quantile mapping (QM) method was employed to produce bias-corrected daily data. Then the future changes in climate extremes were assessed using a subset of extreme temperature and precipitation indices devised by the Expert Team on Climate Change Detection and Indices (ETCCDI). For the assessment of precipitation extremes, Consecutive Wet Days (CWD), Number of days with rainfall greater than 10mm (R10mm), Wet Days Precipitation (R95p), total annual rainfall (PRCPTOT), annual maximum 1-day precipitation (Rx1day), and annual maximum 5-day precipitation (Rx5day) have been utilized while for the temperature extremes, frequency of hot days (TX90p) and cool days (TX10p) have been used. The results from the probability density function (PDF) of most of the precipitation indices show rightward shifting in the future indicating a tendency toward wetter conditions. However, the magnitudes of change were different for the selected CMIP6 Global Climate Models (GCMs). The projected increase in CWD is greater over the south-western region of the country while the projected increase in PRCPTOT is greater over the north-eastern region of the country under all scenarios. R10mm shows the highest increase for the SSP585. In response to climate change, the TX90p shows a general increase in this century. However, the frequency of cool days is projected to decrease for most of the SSP scenarios. The results from these analyses present an opportunity to understand the impact of climate change on extreme events in Bangladesh and thus may help the local decision-makers in policy-making, disaster management, and infrastructure planning.