In inorganic chemistry, the chemical reactions are mostly represented by Inorganic chemical formulas of the chemical compounds. While digitizing the handwritten or printed contents related to inorganic chemistry, firstly it has to recognize handwritten inorganic chemical formulas (HICF). The HICF has represented by using alphabets and numbers, this alphabet or number is termed as Inorganic Symbols (IS). Therefore, to recognize HICF; the inorganic symbols have to be reorganized. Here in this paper, we had developed a model to recognize HICF. The developed model has based on the classification of inorganic symbols (IS). This proposed model does the classification based on geometric shapes, which are part of the IS. The classification of IS has done in three classes based on the geometric shapes used to formulate the IS. After classification, this model identifies the individual IS with the help of feature descriptor and Support Vector Machine (SVM). In this paper, each class has it’s trained SVM to identify individual IS from the respective class. Once each individual IS has identified then it has put together to represent in the inorganic chemical formula. The result shows that the recognition percentage of each SVM is nearly equal to 97%. The system accepts scanned images of HICF as an input and delivers recognized HICF in text format as an output.