In the context of the rapid development of digital education, the assessment of pre-service teachers’ learning ability is of great significance for improving teaching quality and professional development. Traditional assessment methods face challenges such as difficulties in data collection, single-dimensional analysis, and lack of personalization, making it hard to comprehensively reflect teachers’ learning ability. Based on cloud computing and big data technology, this paper constructs an intelligent assessment system for pre-service teachers’ learning ability. The system leverages cloud computing for efficient data storage and computation and integrates big data analysis methods to achieve multi-dimensional data fusion, intelligent analysis, and dynamic assessment. The system architecture includes modules for data collection, data processing, intelligent assessment, and feedback optimization, incorporating machine learning algorithms to enhance assessment accuracy and adaptability. Experimental results demonstrate that the system significantly improves the scientific and intelligent level of assessment, providing accurate data support and decision-making references for the professional development of pre-service teachers. The findings of this study offer strong support for the advancement of educational informatization and provide new insights for the construction of intelligent assessment systems.