<p>Micro machining technology has rapidly developed with the widespread application of miniature components. Chip morphology and burr size are critical indicators for assessing the surface topography in micro machining. However, the evaluation criteria established for macroscopic cutting conditions are no longer applicable in this context. To investigate the effects of cutting parameters on chip morphology and burr size under micro-machining conditions, a typical dual-phase titanium alloy is selected as the workpiece for the micro milling study. First, a physical micro milling experimental platform is established. Next, based on a single-factor experimental approach, the influence of cutting parameters on chip morphology and burr size is analyzed. Finally, top burrs height prediction model of the down and up milling is developed using the SSA-LSSVM algorithm. The results indicate that the cutting depth has a minimal effect on chip morphology. However, as the feed per tooth increases, fine crack-like features become more prominent along the edges of the chips. The cutting depth primarily affects the top burr size in down milling, while the feed per tooth has the least. The prediction accuracy of the SSA-LSSVM models for both the down and up milling reaches 90%, with the maximum prediction errors being 14.2 and 15.1%, respectively. This prediction model can effectively guide the complex nonlinear mapping relationship between cutting parameters and burr size. The research results provide theoretical and experimental basis for the analysis of chip morphology and burr size prediction in micro-milling of dual-phase alloys.</p>