Double-front construction machinery, which has been designed for adaptation to complicated work, demands higher operational skills to control two manipulators with more multiple joints. To handle more complicated machinery skillfully, intelligent systems that can autonomously identify the current work states and also provide cognitive and operational supports to their operators are inevitably required. Particularly, work state identification methods strongly require high reliability and robustness due to the variety of the construction work environment and operatorÂ’s skill level. However, most current construction machinery has unique functions that only reproduce the movements originating from the operator. We therefore addressed the need for a new conceptual design of operator support system and evaluated it using our newly developed simulator. Our experimental results showed that the support system improves the work performance, including decreasing the operational time for completing a task, the number of error operations, and the mental workload on the operators.