Purpose: This study focuses on the causal mechanisms by which a series of organizational factors like commitment, communication, experience, dependence and trust collectively affect on the success of science-industry R&D cooperation. The purpose of this paper is to identify multiple paths of complex causal recipes that can lead to success of science-industry R&D cooperation. Design/methodology/approach: The study uses fuzzy-set qualitative comparative analysis (fsQCA), a technique that provides a holistic view of the examined interrelationships, compared to traditional net effect approaches that assume symmetric and linear relationships among variables. Findings: Results indicate that different causal paths, exactly five configurations, explain success R&D contracts. Particularly, the findings reveal that the availability of commitment and communication are important, sufficient conditions because they appear in at least three of the five configurations that result from the analysis. In this way, a series of conclusions and implications have been obtained that can be very useful, both in the academic world and when trying to lead and manage cooperation agreements. Research implications: A comprehensive theoretical model was developed and tested that identifies the organizational factors of the success of science-industry R&D cooperation. The presented model and comprehensive research using fs/QCA allows to overcome the fragmentation of this specialized literature. Practical implications: The results contain a number of practical recommendations that can be useful in the conduct and management of cooperation agreements. During the establishing and developing contract stages, it is recommended to design managerial and organizational mechanisms that ensure a high degree of commitment and communication in combination with experience (configuration number 1) and/or with dependences (configuration number 4). Originality/value: Vital value of this paper is the use of fs/QCA, a technique that is an important novelty, at least in the field of R&D cooperation relationships between companies and research organizations. This method allows testing the configuration of conditions in relation to a specific outcome (e.g. success of science-industry R&D cooperation) in a way that is not possible using a linear additive approach.