The transportation sector relies heavily on the diesel-operated compression ignition engines. However, the combustion of diesel produces greenhouse gases, which are a major threat to the environment as well as humans. Alternatives to diesel are gaining importance since they can reduce greenhouse gases and address the energy security as well. One such alternative is used cooking oil, which the world is generating in large quantities. The used cooking oil can be easily converted to biodiesel. The biodiesel is produced by the transesterification method. However, studies show that the biodiesel cannot completely replace diesel due to its inherent issues. Another method, namely hydroprocessing, can also convert the used cooking oil into a fuel with properties closer to diesel. In the present chapter, the diesel-like fuel obtained by hydrotreating the used cooking oil was stored for a period of 12 months, and its properties namely kinematic viscosity, density, and calorific value were measured every month. The results suggest that the properties of the fuel were slightly changed and were well within the standard limits even after 12 months. Engine experiments were also carried out, and the effect of the fuel and its blends on the combustion characteristics were studied. The cyclic variations during engine operation were found by calculating the variance coefficient of indicated mean effective pressure (IMEP) for all the loads and test blends. With the addition of hydrotreated oil, the cyclic variations were reduced, and as the percentage increases, the variations reduce further. A neural network was then trained using the Levenberg–Marquardt (LM) algorithm and scaled conjugate gradient (SCG) algorithm. Results reveal that the LM algorithm with 16 neurons resulted in the highest R2 values.