The article develops the problem of credit process management and credit decisions support for small businesses. The official data on crediting and defaulted debt of small businesses is presented and analyzed. A higher growth rate of defaulted debt for small businesses indicates a lower efficiency of applied methods for credit risk assessment and management. For credit process management it is rational to apply (credit) decision support systems. The article systematized the specifics of small business crediting. The key feature is the high level of uncertainty in making credit decisions due to the frequent changes in the regulatory and legal information, a wide range of interpretation of the results of financial ratios analysis, incomplete information because of special (simplified) tax regimes. Taking into consideration specifics of small business crediting, the article proposes requirements for developing decision support systems and a group of tasks which are advisable to implement as system functions. The article systematizes the key decisions (tasks) to be taken at different stages of thr credit process for small businesses and contains a literature review of models and techniques developed and adapted to support decision-making on small business crediting. The majority of the models and techniques discussed in the study were designed or adapted for the Russian conditions and specifics of small business crediting. A composition of the major functional subsystems of the decision support system currently under development is proposed in the article. One of the distinguishing features of the decision support system is the application of hybrid techniques for adapting to both the expert-oriented credit departments and the departments focused on credit history information processing.