Energy has become an indispensable commodity in modern society, serving as a vital resource for communities and diverse sectors of the economy. Its demand spans across multiple essential functions, including electricity generation, transportation, cooking, heating, water pumping, and industrial processing, highlighting its pivotal role in daily life. Consequently, the technologies driving energy production and consumption have garnered unprecedented attention. The selection of energy resources and technologies holds significant sway over both economic development and environmental sustainability. In this context, forecasting the demand for electricity and transport fuel assumes paramount importance. This study employs machine learning models to forecast the country's electricity and transport fuel demand under three distinct scenarios. The electricity demand forecast indicates a projected increase in demand averaging from 3 to 6% annually across the various scenarios considered throughout the outlook period. Similarly, the estimated forecast for transport fuel demand suggests a rise averaging from 6 to 11% annually over the study period. This research would help energy policy and decision makers and stack-holders in formulation of future layout of energy system of Pakistan.