AbstractMagnetic Resonance Spin TomogrAphy in Time‐domain (MR‐STAT) is a multiparametric quantitative MR framework, which allows for simultaneously acquiring quantitative tissue parameters such as T1, T2, and proton density from one single short scan. A typical two‐dimensional (2D) MR‐STAT acquisition uses a gradient‐spoiled, gradient‐echo sequence with a slowly varying RF flip‐angle train and Cartesian readouts, and the quantitative tissue maps are reconstructed by an iterative, model‐based optimization algorithm. In this work, we design a three‐dimensional (3D) MR‐STAT framework based on previous 2D work, in order to achieve better image signal‐to‐noise ratio, higher though‐plane resolution, and better tissue characterization. Specifically, we design a 7‐min, high‐resolution 3D MR‐STAT sequence, and the corresponding two‐step reconstruction algorithm for the large‐scale dataset. To reduce the long acquisition time, Cartesian undersampling strategies such as SENSE are adopted in our transient‐state quantitative framework. To reduce the computational burden, a data‐splitting scheme is designed for decoupling the 3D reconstruction problem into independent 2D reconstructions. The proposed 3D framework is validated by numerical simulations, phantom experiments, and in vivo experiments. High‐quality knee quantitative maps with 0.8 × 0.8 × 1.5 mm³ resolution and bilateral lower leg maps with 1.6 mm isotropic resolution can be acquired using the proposed 7‐min acquisition sequence and the 3‐min‐per‐slice decoupled reconstruction algorithm. The proposed 3D MR‐STAT framework could have wide clinical applications in the future.