By introducing emerging digital technologies, this study effectively addresses the current challenge of vocational college students’ career guidance and entrepreneurship support being disconnected from the talent market. The article is based on the decision tree method in data mining, proposing appropriate decision factor extraction methods tailored to data samples from the employment market and entrepreneurial experiences. A prediction model combining the C4.5 algorithm and CART algorithm is constructed to forecast career and entrepreneurial tendencies, and based on the prediction results, intervention pathways for ideological and political education are proposed. Through the constructed decision tree, the C4.5 algorithm achieved the highest F-value of 0.841 in predicting students’ employment tendencies. After the integration of ideological and political education, 88.65% of students believed it could help them further enhance their understanding of future career planning. The data-driven method proposed in this paper for addressing employment and entrepreneurship issues among vocational college graduates has achieved certain.