Dyslexia is a learning disorder characterized by difficulties in reading and writing, despite individuals having normal intelligence. This study aims to develop an integrated application based on machine learning and the phonics method to enhance the literacy skills of children with dyslexia. The developed application, namely DISAPP, integrates optical character recognition (OCR) and text-to-speech (TTS) technology to assist users in recognizing and understanding text more effectively. The research method employed is Research and Development (R&D) using the four-D approach, which includes the stages of definition, design, development, and dissemination. Application testing showed a significant improvement in the reading and writing skills of children with dyslexia, with a system accuracy rate reaching 99% in text recognition. Additionally, evaluation through the system usability scale (SUS) yielded 87.2 score, indicating a very high level of usability. The implementation of this application also positively impacted parents’ understanding of dyslexia and increased children’s enthusiasm for learning. The findings of this study confirm that the integration of machine learning technology and the phonics method can serve as an innovative solution for improving literacy in children with dyslexia, while also opening opportunities for more effective educational approaches.