Drag reduction is one of the main problems in aircraft design and a meaningful way to save fuel and improve efficiency. Surface microgrooves can reduce the frictional resistance of aircraft walls and become one of the main ways to reduce aircraft drag. A nanosecond laser can prepare microgrooves. However, the recast layers under high laser energy during processing deteriorate the processing quality. How to improve processing quality while ensuring processing efficiency is a challenge. By replacing the target feature analysis model in the original genetic algorithm with an optimization target model based on the response surface method, this study proposes an optimization method for the nanosecond laser processing of the microgroove. This method uses the difficult-to-machine aerospace material TC4 titanium alloy as the target. The Box–Behnken design method is used to design the laser processing experiment of the microgroove. The validity and reliability of the proposed optimization method are verified. It is worth mentioning that the proposed method can obtain satisfactory optimization results with fewer parameter variables and fewer experiments, with low experimental cost and high optimization efficiency compared to genetic algorithms. Furthermore, the optimized process parameters will provide initial parameters for the high-quality preparation of large-scale microgrooves on the TC4 surface through the nanosecond pulsed laser layer-by-layer scanning processing way. And the optimization method is suitable for optimizing short-pulse and long-pulse laser processing parameters of microgrooves on metal surfaces and has practical engineering value.