Diamond-like carbon (DLC) is becoming increasingly popular due to its several superior mechanical, chemical, tribological and optical properties. However, achievement of these advantageous properties of DLC coatings mainly depends on various input parameters involved in its deposition process. Recently,the DLC researchers have started tapping the potential of different optimization techniques for its better design, functionality and applicability. In this paper, three optimization tools, i.e. weighted-sum multi-objective optimization, Pareto multi-criteria decision making (MCDM) technique and optimal prediction based on level averaging post-MCDM are applied for determination of the optimal parametric combination of a thermal chemical vapor deposition (CVD) process for better DLC application. It is observed that the choice of the optimization technique has a significant role on the optimal DLC performance. The observations are reported based on 20 experiments of DLC deposition on silicon substrates using thermal CVD process. The optimal settings of deposition temperature, and hydrogen and acetylene flow rates are identified based on simultaneous optimization of two tribological properties, i.e. coefficient of friction and wear rate of the DLC coatings. It is propounded that the Pareto MCDM technique can provide the most balanced solution.