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Particle-laden flow prediction requires accurate fluid-force modeling. Nevertheless, a reliable and practicle force model for finite-size particles in turbulent flows is still missing. In the present work, a fluid force model for a finite-size particle in turbulence is developed by simu lating turbulent flow past a stationary spherical particle using particle-resolved direct numerical simulation (PRDNS). A uniform mean flow and homogeneous isotropic turbulence are super posed to generate the inflow, and the turbulence is preserved to be statistically stationary in the entire flow field by external forcing. A concurrent precursor approach is adopted to remove the impact of particle wake on inflow caused by the periodic boundary condition. Throughout the simulation, a broad range of the non-dimensional parameters is covered: the particle Reynolds number is set to 1∼100, the scale ratio between the particle size and the Kolmogorov scale is 0∼30, and the velocity ratio between the turbulence velocity fluctuation intensity and the mean slip velocity is 0∼50. Our simulation demonstrates that turbulence increases the mean drag force of the particle, which is consistent with previous studies. By fitting the PRDNS data as a function of the particle Reynolds number, scale ratio, and velocity ratio, an empirical correlation for the mean drag force is obtained. Furthermore, we find that the fluctuations of both the drag and lateral forces follow the Gaussian distribution. Consequently, the temporal variations of the f luctuating drag and lateral forces are modeled using a stochastic Langevin equation. Empirical correlations of the fluctuation intensities and time scales involved in the stochastic model are also determined by fitting the PRDNS data. Finally, a finite-size particle moving in turbulence is simulated to test the proposed stochastic model.