The research aims to study the petition of three-entry bookkeeping carry by key areas of artificial intelligence namely machine learning techniques in an integrated mode and its impact on intensify the transparency and trustiness of financial records in organizations .The research problem lies in the challenges facing customary accounting systems, namely weak translucence and the chance for manipulation of accounting information, in light of the rapid grilled transformation. This highlights the need to embrace the latest accounting systems and leverage technological advancements, especially in the domain of artificial intelligence, and to pursue for integration between them to achieve the best modern accounting frameworks. The descriptive-analytical approach was adopted due to its suitability to the research variables Data were collected in the field using the most common statistical tool the reconnaissance which was meant according to the five-point Likert scale It was distributed to a sample of employees in the accounting and auditing field, where the number of returned questionnaires valid for statistical analysis was 92 questionnaires out of 100 questionnaires , The SPSS program was used to analyze the echo of the model members through adjectival statistics, Pearson correlation coefficient, and simple and multiple regression analysis to test the research hypotheses. The results showed statistically significant relationships between the application of three-entry bookkeeping and the transparency of financial records as well as between the use of machine learning techniques and the reliability of financial records, The results also showed that the integration of three-entry bookkeeping and machine learning techniques redound positively to refinement the credibility of financial records in general and improvement the quality of accounting information, by perfection the rigor of information, decrease errors, and enhancing confidence in the outputs of the accounting system.