The CAPTAIN Toolbox is a collection of Matlab algorithmic routines for time series analysis, forecasting and control. It is intended for system identification, signal extraction, interpolation, forecasting and control of a wide range of linear and non-linear stochastic systems across science, engineering and the social sciences. This article briefly reviews the main features of the Toolbox, outlines some recent developments and presents a number of examples that demonstrate the performance of these new routines. The examples range from consideration of global climate data, through to electro-mechanical systems and broiler chicken growth rates. The new version of the Toolbox consists of the following three modules that can be installed independently or together: off-line, time-varying parameter estimation routines for Unobserved Component (UC) modelling and forecasting; Refined Instrumental Variable (RIV) algorithms for the identification and estimation of both discrete and hybrid continuous-time transfer function models; and various routines for Non-Minimal State Space (NMSS) feedback control system design. This new segmented approach is designed to provide new users with a gentler introduction to Toolbox functionality; one that focuses on their preferred application area. It will also facilitate more straightforward incorporation of novel algorithms in the future.