This paper presents a randomized method for simulating Lindblad equations and thermal state preparation. The method uses a single randomly sampled Lindbladian at each time step, significantly simplifying the implementation of Lindblad dynamics, especially for quantum many-body systems with a large or infinite number of jump operators. The approach is inspired by the qDRIFT method used in Hamiltonian simulation and is generalized to open quantum systems. The method is particularly useful for quantum Gibbs sampling, where the Lindblad dynamics is used to prepare a specific Gibbs state. Unlike deterministic methods that require numerous jump operators to ensure ergodicity, the randomized approach simplifies the implementation by using a single randomly sampled jump operator. The paper provides a detailed convergence analysis for the proposed randomized method, considering both the average and typical realizations of the algorithm. The method is shown to ensure fast thermalization of Hamiltonian systems characterized by random Pauli strings, where the spectral density closely adheres to the semi-circle law. The paper also discusses the application of the method to the construction of a random Davies generator, which is used for efficient thermalization in quantum Gibbs sampling. The analysis shows that the spectral gap of the random Davies generator scales as Ω(β⁻³/²), where β is the inverse temperature of the system. The method is demonstrated to be effective for Hamiltonians that approximately follow the semi-circle law, providing a fast mixing guarantee for such systems. The paper concludes with a discussion of future directions, including the exploration of high-order randomized methods and the design of ensembles of jump operators that capture both the spectral and spatial structures of the Hamiltonians.This paper presents a randomized method for simulating Lindblad equations and thermal state preparation. The method uses a single randomly sampled Lindbladian at each time step, significantly simplifying the implementation of Lindblad dynamics, especially for quantum many-body systems with a large or infinite number of jump operators. The approach is inspired by the qDRIFT method used in Hamiltonian simulation and is generalized to open quantum systems. The method is particularly useful for quantum Gibbs sampling, where the Lindblad dynamics is used to prepare a specific Gibbs state. Unlike deterministic methods that require numerous jump operators to ensure ergodicity, the randomized approach simplifies the implementation by using a single randomly sampled jump operator. The paper provides a detailed convergence analysis for the proposed randomized method, considering both the average and typical realizations of the algorithm. The method is shown to ensure fast thermalization of Hamiltonian systems characterized by random Pauli strings, where the spectral density closely adheres to the semi-circle law. The paper also discusses the application of the method to the construction of a random Davies generator, which is used for efficient thermalization in quantum Gibbs sampling. The analysis shows that the spectral gap of the random Davies generator scales as Ω(β⁻³/²), where β is the inverse temperature of the system. The method is demonstrated to be effective for Hamiltonians that approximately follow the semi-circle law, providing a fast mixing guarantee for such systems. The paper concludes with a discussion of future directions, including the exploration of high-order randomized methods and the design of ensembles of jump operators that capture both the spectral and spatial structures of the Hamiltonians.