A sensor (microphone) placement method based on mutual information for spatial sound field recording is proposed. The sound field recording methods using distributed sensors enable the estimation of the sound field inside a target region of arbitrary shape; however, it is a difficult task to find the best placement of sensors. We focus on the mutual-information-based sensor placement method in which spatial phenomena are modeled as a Gaussian process (GP). We propose the use of the sound-field-interpolation kernel for the covariance of measurements in a GP model to obtain the sensor placement suitable for sound field recording. We also extend the method to treat broadband signals and derive an efficient algorithm based on block matrix inversion. Numerical simulation results indicated that the proposed method achieves accurate sound field estimation compared with a method using the generally used Gaussian kernel.