In traditional fixed-direction 3D printing, complex geometric models require support structures for large overhanging regions, leading to difficulties in removal, surface damage, and material waste. This study proposes a model decomposition algorithm for multi-axis 3D printing, aiming to divide the model into sub-regions requiring no or minimal support, which are printed sequentially via intermittent rotation of the print platform using a multi-DOF 3D printing device. Our algorithm employs a heuristic optimization method to minimize overhanging area and decomposition steps, leveraging Pareto multi-objective optimization to compute the Pareto front and adopting a beam search strategy to generate decomposition sequences. Decomposition and printing experiments on complex models demonstrate the method’s effectiveness in significantly reducing computational time, support requirements, and material costs while improving printing efficiency, enabling effective support-free multi-axis 3D printing.