The Holy Quran is undoubtedly one of the most important books for all the Arabic/Islamic People, covering too many concepts and topics which guide all the Muslims in their life, behaviors, and acts of devotion. This Project is developed to help all Muslims to deal with the Holy Quran easier and faster. as this Project allow them to search the Quran for specific Keyword or Verse, and for a Concrete Topic or Conceptual Topic which is a challenging task. It also helps them in its Memorization and Recitation. This project consists of two parts; the first is a concept-based Search Engine for Holy Quran based on a Deep Learning Model called 'word2vec' used to search in the Quran using topic or concept with accuracy about 70%. This search engine is built through four phases. First one is to build a new Quran dataset in which we annotated each verse with it's related topic using Mushaf Al-Takweed, Second, we collect large classic Arabic corpus which is about 40 million words, then we trained our word2vec model using this corpus, third, we get the vector of each topic in our dataset and query's vector using our word2vec model. Finally, we get the most relevant topic by calculating the cosine similarity between query's vector and topics' vectors and retrieve its verses from our dataset. We calculated our system's accuracy by collecting about 300 queries using google form and tried them on our system which could satisfied about 70% of these queries. The second part is an iOS Mobile Application which used to introduce the search tool and, also, to help users memorize and recite the Quran using voice and help them know their mistakes. This system has high accuracy in evaluating users' sayings in comparison of other applications.