Pseudouridine (Ψ) is the first discovered and the most abundant RNA modification that has been widely study in the past decades. Ψ is very important to various kinds of RNA, such as rRNA, tRNA and mRNA. To identify potential Ψ sites in RNA sequence, the laborious and high cost experimental approaches have some limitations, such as its limited coverage. Alternatively, the computational methods for Ψ site prediction provide a more cost-effective avenue. Only two sequence-based models was available in the field of mouse Ψ site prediction, and therefore, it is highly desirable to propose a high-accuracy model using additional genomic features. In our study, a high-accuracy prediction framework PSI-Mouse was established for Ψ site prediction in mouse transcriptome. Beside the conventional sequence-derived features, PSI-Mouse firstly introduced 38 additional genomic features to the prediction model, and achieved satisfactory improvement in the prediction accuracy. Furthermore, PSI-Mouse also provides gene annotations and various post-transcriptional analysis, and 3282 experiment-validated mouse Ψ sites were included with query function, which serves as a useful tool to explore the underlying regulatory mechanisms of computationally predicted Ψ sites. The server is freely available at: http://180.208.58.66/PSI-Mouse