Drawing on the Harris-Todaro model and push–pull theory, this study investigates how anticipated gig-economy earnings shape the occupational mobility of China’s new-generation rural migrant workforce. Using panel data from the China Labor-Force Dynamics Survey (2014–2018), we apply ordinary least squares, binary logit, and instrumental-variable techniques to assess the influence of expected gig income on sectoral transitions. Our results demonstrate that higher expected gig earnings significantly alter mobility choices across sectors, thereby promoting overall occupational movement. When focusing on individuals initially engaged in formal employment, however, anticipated gig income exerts a significantly negative effect on their propensity to change occupations. Mechanism analysis further reveals that improvements in expected gig earnings translate into enhanced health status, which in turn mediates occupational mobility decisions. Finally, a moderation analysis incorporating provincial-level variables for Shaanxi indicates that elevated regional unemployment rates substantially constrain mobility among this cohort. In light of these findings, we recommend establishing a comprehensive gig-employment service infrastructure, fostering a transparent and equitable labor market, and encouraging continuous human-capital investment among rural migrants to facilitate more rational and dynamic occupational flows.