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<article article-type="research-article" dtd-version="1.2" xml:lang="ru" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><front><journal-meta><journal-id journal-id-type="issn">2518-1092</journal-id><journal-title-group><journal-title>Research result. Information technologies</journal-title></journal-title-group><issn pub-type="epub">2518-1092</issn></journal-meta><article-meta><article-id pub-id-type="doi">10.18413/2518-1092-2025-10-4-0-2</article-id><article-id pub-id-type="publisher-id">4012</article-id><article-categories><subj-group subj-group-type="heading"><subject>AUTOMATION AND CONTROL</subject></subj-group></article-categories><title-group><article-title>&lt;strong&gt;MOBILE PLATFORM FOR EXPENSE CONTROL AND VEHICLE MAINTENANCE PLANNING USING MACHINE LEARNING METHODS&lt;/strong&gt;</article-title><trans-title-group xml:lang="en"><trans-title>&lt;strong&gt;MOBILE PLATFORM FOR EXPENSE CONTROL AND VEHICLE MAINTENANCE PLANNING USING MACHINE LEARNING METHODS&lt;/strong&gt;</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Duhovnikov</surname><given-names>Vadim Aleksandrovich</given-names></name><name xml:lang="en"><surname>Duhovnikov</surname><given-names>Vadim Aleksandrovich</given-names></name></name-alternatives><email>robin.homenson@mail.ru</email></contrib><contrib contrib-type="author"><name-alternatives><name xml:lang="ru"><surname>Abramova</surname><given-names>Oksana Fedorovna</given-names></name><name xml:lang="en"><surname>Abramova</surname><given-names>Oksana Fedorovna</given-names></name></name-alternatives><email>oxabra@yandex.ru</email></contrib></contrib-group><pub-date pub-type="epub"><year>2025</year></pub-date><volume>10</volume><issue>4</issue><fpage>0</fpage><lpage>0</lpage><self-uri content-type="pdf" xlink:href="/media/information/2025/4/ИТ_НР_10_4_2.pdf" /><abstract xml:lang="ru"><p>In today&amp;#39;s world, mobile technologies play a key role in everyday life, greatly simplifying the performance of various tasks. This fully applies to amateur motorists, for whom timely and accurate information can improve safety, comfort and efficiency of driving. This paper presents the design and development process of a mobile application that stands out among similar software products by implementing personalized expert recommendations. With the growing need for localized solutions for the Russian market, this application offers a comprehensive approach that includes a system of expert recommendations based on machine learning techniques, as well as the use of personalized data about users, their vehicles and vehicle maintenance costs to create recommendations aimed at optimizing maintenance and improving forecast accuracy. The mobile app consists of several functional modules such as vehicle management, expense analysis, notifications and the MA Live social section. This creates a single space for efficient management of vehicle operation, meeting the needs of both regular users and those focused on social interaction in the automotive community. The developed system uses prediction methods based on vehicle data, vehicle operation and owner behavior using a machine learning model.</p></abstract><trans-abstract xml:lang="en"><p>In today&amp;#39;s world, mobile technologies play a key role in everyday life, greatly simplifying the performance of various tasks. This fully applies to amateur motorists, for whom timely and accurate information can improve safety, comfort and efficiency of driving. This paper presents the design and development process of a mobile application that stands out among similar software products by implementing personalized expert recommendations. With the growing need for localized solutions for the Russian market, this application offers a comprehensive approach that includes a system of expert recommendations based on machine learning techniques, as well as the use of personalized data about users, their vehicles and vehicle maintenance costs to create recommendations aimed at optimizing maintenance and improving forecast accuracy. The mobile app consists of several functional modules such as vehicle management, expense analysis, notifications and the MA Live social section. This creates a single space for efficient management of vehicle operation, meeting the needs of both regular users and those focused on social interaction in the automotive community. The developed system uses prediction methods based on vehicle data, vehicle operation and owner behavior using a machine learning model.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>mobile application</kwd><kwd>design</kwd><kwd>software development</kwd><kwd>personalization</kwd><kwd>forecasting</kwd></kwd-group><kwd-group xml:lang="en"><kwd>mobile application</kwd><kwd>design</kwd><kwd>software development</kwd><kwd>personalization</kwd><kwd>forecasting</kwd></kwd-group></article-meta></front><back><ref-list><title>Список литературы</title><ref id="B1"><mixed-citation>1. Lunchenkova E.V. Trends and Prospects for the Development of the Global Mobile Application Market / E.V. Lunchenkova, K.I. 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