Julia is a dynamic language for scientific computing. For a dynamic language, Julia is surprisingly typefull. Types are used not only to structure data but also to guide dynamic dispatch – the main design tool in the language. No matter the dynamism, Julia is performant: flexibility is compiled away at the run time using a simple but smart type-specialization based optimization technique called type stability. Based on a model of a JIT mimicking Julia from previous works, we present the first algorithm to approximate type stability of Julia code. Implementation and evaluation of the algorithm is still a work in progress.