In this paper we consider some stochastic bottleneck linear prograrnming problems. In the case when the coefficients of the objective functions are simple randomized, the minimum-risk approach will be used for solving these problems. We prove that, under some positivity conditions, these stochastic problems are reduced to certain deterministic bottleneck linear problems. Applications of these problems to the bottleneck spanning tree problems and bottleneck investment allocation problems are given. A simple numerical example is presented.