This paper introduces a novel neutrosophic inference model for the field of bioinformatics. The model is applied to develop a robust model for precise comparisons of human nucleic acids, where a new DNA sequence is matched against a comprehensive database of old nucleic acids. The results are analyzed in terms of accuracy, certainty, uncertainty, impartiality, and neutrality. Although the proposed model obtained an average accuracy rate of 33% in some cases, the similarities between sequences indicating its ability to accurately with a high accuracy rate of 85% for dissimilarity which highlights its effectiveness in distinguishing dissimilar sequences. However, the neutrality criterion yielding 0% in some cases may raise concerns about potential biases in the model's results towards specific samples. Further research is needed to understand the factors influencing neutrality and improve it for unbiased results. In conclusion, this study emphasizes the importance of employing neutrosophic inference models in the field of bioinformatics. It establishes a reliable benchmark for future nucleic acid comparisons, paving the way for advanced and more comprehensive applications in sequence analysis and genomic research.