Diffusion tensor imaging (DTI) of the brain provides essential information on the white matter integrity and structural connectivity. However, it suffers from a low signal-to-noise ratio (SNR) and requires a long scan time to achieve high spatial and/or diffusion resolution and wide brain coverage. With recent advances in parallel and simultaneous multislice (multiband) imaging, the SNR efficiency has been improved by reducing the repetition time (TR ). However, due to the limited number of RF coil channels available on preclinical MRI scanners, simultaneous multislice acquisition has not been practical. In this study, we demonstrate the ability of multiband DTI to acquire high-resolution data of the mouse brain with 84 slices covering the whole brain in 0.2 mm isotropic resolution without a coil array at 9.4 T. Hadamard-encoding four-band pulses were used to acquire four slices simultaneously, with the reduction in the TR maximizing the SNR efficiency. To overcome shot-to-shot phase variations, Hadamard decoding with a self-calibrated phase was developed. Compared with single-band DTI acquired with the same scan time, the multiband DTI leads to significantly increased SNR by 40% in the white matter. This SNR gain resulted in reduced variations in fractional anisotropy, mean diffusivity, and eigenvector orientation. Furthermore, the cerebrospinal fluid signal was attenuated, leading to reduced free-water contamination. Without the need for a high-density coil array or parallel imaging, this technique enables highly efficient preclinical DTI that will facilitate connectome studies.